LBI

Norway Loster 8c FU25

Norway Loster 8c FU25 Males

Los datos del ciclo vital recogidos de la literatura son:

\(L_{mat}^{LIT}\) = 25.0 mm. Machos, FU 16 (González Herraiz, 2011). Tomo de nuestro muestreo FU 16 y x FUs cercanas.

\(L_{inf}^{LIT}\) = 86.0 mm. Machos, FU 31 (Distribución de tallas, 2014).

\({M/k}^{LIT}\) = 1.9 (Prince et al., 2015).

wal <- read.csv("25_Males_w.csv", stringsAsFactors = FALSE)
head(wal)

##   MeanLength     X1982     X1983     X1984     X1985     X1986     X1987
## 1         19  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518
## 2         20  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757
## 3         21  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248
## 4         22  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448
## 5         23  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854
## 6         24 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999
##       X1988     X1989     X1990     X1991     X1992     X1993     X1994
## 1  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518
## 2  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757
## 3  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248
## 4  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448
## 5  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854
## 6 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999
##       X1995     X1996     X1997     X1998     X1999     X2000     X2001
## 1  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518
## 2  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757
## 3  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248
## 4  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448
## 5  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854
## 6 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999
##       X2002     X2003     X2004     X2005     X2006     X2007     X2008
## 1  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518
## 2  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757
## 3  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248
## 4  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448
## 5  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854
## 6 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999
##       X2009     X2010     X2011     X2012     X2013     X2014     X2015
## 1  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518  5.069518
## 2  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757  5.936757
## 3  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248  6.900248
## 4  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448  7.965448
## 5  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854  9.137854
## 6 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999 10.422999
##       X2016     X2017     X2018     X2019
## 1  5.069518  5.069518  5.069518  5.069518
## 2  5.936757  5.936757  5.936757  5.936757
## 3  6.900248  6.900248  6.900248  6.900248
## 4  7.965448  7.965448  7.965448  7.965448
## 5  9.137854  9.137854  9.137854  9.137854
## 6 10.422999 10.422999 10.422999 10.422999

freq <- read.csv("25_Males.csv",  stringsAsFactors = FALSE)
head(freq)

##   MeanLength X1982  X1983 X1984 X1985 X1986 X1987 X1988 X1989 X1990 X1991 X1992
## 1         19    NA   8148    NA    NA  5570    NA    NA    NA    NA    NA    NA
## 2         20  1059   4154    NA 15621     0    NA    NA    NA    NA    NA    NA
## 3         21  3886    273    NA     0     0    NA    NA    NA    NA  1064    NA
## 4         22  4968  27978    NA     0 14601   440    NA    NA    NA     0    NA
## 5         23 17598  38825  9482 32234 26483  6506  3623    NA  1624 11625    NA
## 6         24 10263 136660 65080 50657 61017  3432   735    NA  2552 11935 12802
##   X1993 X1994 X1995 X1996 X1997 X1998 X1999 X2000 X2001 X2002 X2003 X2004 X2005
## 1  4949    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 2 34637    NA    NA   438    NA    NA   301    NA    NA    NA    NA    NA    NA
## 3 49328    NA    NA   822    NA    NA     0    NA    NA    NA    NA    NA    NA
## 4 29690   715   628  1558  3748    NA   344    NA    NA    NA    NA   858   269
## 5 14845  5640     0    76  1125   358     0   286    NA   204    NA   375   467
## 6 75433  5303   651 14123  5902   366  2177   855    NA   756    77   936   776
##   X2006 X2007 X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015 X2016 X2017 X2018
## 1    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 2    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 3    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 4   122   527    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5   234   310    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA 16.70
## 6   238   294    90    NA    NA    NA    NA    NA    NA    NA    NA    NA 19.66
##   X2019
## 1    NA
## 2    NA
## 3    NA
## 4    NA
## 5    NA
## 6    NA

bin_plot(freq, 1, "cm")

lb_tableSH(freq, 1, "mm", linf = 86.0 , lmat = 25.0 , mk_ratio = 1.90 ,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.22	1.30	0.57	0.00	0.70	0.88
1983	1.06	1.18	0.55	0.00	0.66	0.89
1984	1.14	1.22	0.57	0.00	0.67	0.87
1985	1.14	1.22	0.57	0.00	0.68	0.88
1986	1.22	1.26	0.55	0.00	0.69	0.87
1987	1.26	1.26	0.57	0.00	0.72	0.89
1988	1.30	1.34	0.57	0.00	0.72	0.87
1989	1.34	1.42	0.62	0.01	0.78	0.92
1990	1.22	1.30	0.59	0.00	0.70	0.88
1991	1.10	1.22	0.54	0.00	0.65	0.86
1992	1.26	1.30	0.56	0.00	0.71	0.87
1993	1.26	1.30	0.57	0.00	0.72	0.89
1994	1.18	1.26	0.57	0.00	0.70	0.89
1995	1.18	1.30	0.56	0.00	0.70	0.89
1996	1.22	1.30	0.60	0.01	0.71	0.89
1997	1.18	1.30	0.55	0.00	0.68	0.87
1998	1.34	1.38	0.60	0.00	0.76	0.90
1999	1.18	1.26	0.59	0.00	0.70	0.90
2000	1.26	1.34	0.62	0.01	0.72	0.88
2001	1.26	1.30	0.58	0.00	0.71	0.88
2002	1.26	1.34	0.65	0.01	0.74	0.91
2003	1.38	1.46	0.70	0.03	0.81	0.94
2004	1.26	1.38	0.72	0.03	0.78	0.96
2005	1.26	1.34	0.69	0.02	0.75	0.92
2006	1.30	1.38	0.76	0.04	0.78	0.94
2007	1.30	1.42	0.64	0.01	0.77	0.92
2008	1.42	1.50	0.73	0.04	0.84	0.97
2009	1.50	1.62	0.83	0.14	0.93	1.03
2010	1.34	1.46	0.71	0.04	0.83	0.98
2011	1.50	1.58	0.72	0.04	0.83	0.92
2012	1.58	1.58	0.67	0.02	0.88	0.94
2013	1.54	1.46	0.68	0.02	0.85	0.92
2014	1.38	1.42	0.69	0.02	0.78	0.91
2015	1.34	1.38	0.61	0.00	0.76	0.90
2016	1.38	1.42	0.60	0.00	0.75	0.88
2017	1.34	1.46	0.63	0.01	0.79	0.93
2018	1.46	1.50	0.68	0.02	0.82	0.92
2019	1.38	1.46	0.60	0.00	0.77	0.89

# Primero infraestimando (${M/k}^{LIT}$ multiplicado por 0.75):

lb_tableSH(freq, 1, "mm", linf=86.0, lmat=25.0, mk_ratio=0.75*1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.22	1.30	0.57	0.00	0.64	0.83
1983	1.06	1.18	0.55	0.00	0.59	0.82
1984	1.14	1.22	0.57	0.00	0.61	0.81
1985	1.14	1.22	0.57	0.00	0.61	0.82
1986	1.22	1.26	0.55	0.00	0.63	0.81
1987	1.26	1.26	0.57	0.00	0.65	0.83
1988	1.30	1.34	0.57	0.00	0.65	0.82
1989	1.34	1.42	0.62	0.00	0.70	0.87
1990	1.22	1.30	0.59	0.00	0.64	0.83
1991	1.10	1.22	0.54	0.00	0.59	0.80
1992	1.26	1.30	0.56	0.00	0.64	0.82
1993	1.26	1.30	0.57	0.00	0.65	0.83
1994	1.18	1.26	0.57	0.00	0.63	0.83
1995	1.18	1.30	0.56	0.00	0.63	0.83
1996	1.22	1.30	0.60	0.00	0.64	0.83
1997	1.18	1.30	0.55	0.00	0.62	0.81
1998	1.34	1.38	0.60	0.00	0.68	0.85
1999	1.18	1.26	0.59	0.00	0.63	0.84
2000	1.26	1.34	0.62	0.00	0.65	0.83
2001	1.26	1.30	0.58	0.00	0.64	0.82
2002	1.26	1.34	0.65	0.00	0.67	0.85
2003	1.38	1.46	0.70	0.01	0.73	0.89
2004	1.26	1.38	0.72	0.02	0.71	0.90
2005	1.26	1.34	0.69	0.01	0.68	0.87
2006	1.30	1.38	0.76	0.02	0.71	0.89
2007	1.30	1.42	0.64	0.00	0.69	0.87
2008	1.42	1.50	0.73	0.02	0.76	0.91
2009	1.50	1.62	0.83	0.07	0.84	0.98
2010	1.34	1.46	0.71	0.01	0.75	0.92
2011	1.50	1.58	0.72	0.02	0.75	0.88
2012	1.58	1.58	0.67	0.00	0.79	0.90
2013	1.54	1.46	0.68	0.00	0.77	0.88
2014	1.38	1.42	0.69	0.01	0.70	0.86
2015	1.34	1.38	0.61	0.00	0.69	0.85
2016	1.38	1.42	0.60	0.00	0.68	0.83
2017	1.34	1.46	0.63	0.00	0.71	0.88
2018	1.46	1.50	0.68	0.01	0.74	0.87
2019	1.38	1.46	0.60	0.00	0.69	0.84

# Segundo sobrestimando (${M/k}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 1, "mm", linf=86.0, lmat=25.0, mk_ratio=1.25*1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.22	1.30	0.57	0.01	0.77	0.92
1983	1.06	1.18	0.55	0.00	0.72	0.94
1984	1.14	1.22	0.57	0.01	0.74	0.92
1985	1.14	1.22	0.57	0.01	0.75	0.93
1986	1.22	1.26	0.55	0.00	0.76	0.91
1987	1.26	1.26	0.57	0.00	0.79	0.93
1988	1.30	1.34	0.57	0.01	0.80	0.91
1989	1.34	1.42	0.62	0.02	0.85	0.96
1990	1.22	1.30	0.59	0.01	0.77	0.92
1991	1.10	1.22	0.54	0.00	0.71	0.91
1992	1.26	1.30	0.56	0.00	0.78	0.91
1993	1.26	1.30	0.57	0.00	0.79	0.93
1994	1.18	1.26	0.57	0.01	0.77	0.94
1995	1.18	1.30	0.56	0.00	0.77	0.94
1996	1.22	1.30	0.60	0.01	0.78	0.93
1997	1.18	1.30	0.55	0.00	0.75	0.91
1998	1.34	1.38	0.60	0.01	0.83	0.94
1999	1.18	1.26	0.59	0.01	0.77	0.94
2000	1.26	1.34	0.62	0.02	0.79	0.92
2001	1.26	1.30	0.58	0.01	0.78	0.92
2002	1.26	1.34	0.65	0.03	0.81	0.95
2003	1.38	1.46	0.70	0.06	0.89	0.98
2004	1.26	1.38	0.72	0.06	0.86	1.01
2005	1.26	1.34	0.69	0.04	0.82	0.96
2006	1.30	1.38	0.76	0.07	0.86	0.98
2007	1.30	1.42	0.64	0.03	0.84	0.97
2008	1.42	1.50	0.73	0.10	0.93	1.00
2009	1.50	1.62	0.83	0.25	1.03	1.07
2010	1.34	1.46	0.71	0.10	0.91	1.02
2011	1.50	1.58	0.72	0.08	0.91	0.95
2012	1.58	1.58	0.67	0.06	0.96	0.97
2013	1.54	1.46	0.68	0.07	0.93	0.96
2014	1.38	1.42	0.69	0.04	0.86	0.95
2015	1.34	1.38	0.61	0.01	0.83	0.94
2016	1.38	1.42	0.60	0.01	0.83	0.91
2017	1.34	1.46	0.63	0.02	0.86	0.97
2018	1.46	1.50	0.68	0.06	0.90	0.96
2019	1.38	1.46	0.60	0.01	0.84	0.93

# Tercero usando el valor por defecto de 1.5.

lb_tableSH(freq, 1, "m", linf=86.0, lmat=25.0, mk_ratio=1.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.22	1.30	0.57	0.00	0.65	0.84
1983	1.06	1.18	0.55	0.00	0.60	0.83
1984	1.14	1.22	0.57	0.00	0.62	0.82
1985	1.14	1.22	0.57	0.00	0.62	0.83
1986	1.22	1.26	0.55	0.00	0.64	0.82
1987	1.26	1.26	0.57	0.00	0.66	0.84
1988	1.30	1.34	0.57	0.00	0.67	0.83
1989	1.34	1.42	0.62	0.00	0.71	0.88
1990	1.22	1.30	0.59	0.00	0.65	0.84
1991	1.10	1.22	0.54	0.00	0.60	0.81
1992	1.26	1.30	0.56	0.00	0.65	0.83
1993	1.26	1.30	0.57	0.00	0.66	0.84
1994	1.18	1.26	0.57	0.00	0.64	0.84
1995	1.18	1.30	0.56	0.00	0.64	0.84
1996	1.22	1.30	0.60	0.00	0.65	0.84
1997	1.18	1.30	0.55	0.00	0.63	0.82
1998	1.34	1.38	0.60	0.00	0.70	0.86
1999	1.18	1.26	0.59	0.00	0.64	0.85
2000	1.26	1.34	0.62	0.00	0.66	0.84
2001	1.26	1.30	0.58	0.00	0.66	0.83
2002	1.26	1.34	0.65	0.01	0.68	0.86
2003	1.38	1.46	0.70	0.01	0.74	0.90
2004	1.26	1.38	0.72	0.02	0.72	0.92
2005	1.26	1.34	0.69	0.01	0.69	0.88
2006	1.30	1.38	0.76	0.03	0.72	0.90
2007	1.30	1.42	0.64	0.00	0.70	0.88
2008	1.42	1.50	0.73	0.02	0.77	0.92
2009	1.50	1.62	0.83	0.08	0.86	0.99
2010	1.34	1.46	0.71	0.01	0.76	0.93
2011	1.50	1.58	0.72	0.02	0.76	0.88
2012	1.58	1.58	0.67	0.00	0.81	0.90
2013	1.54	1.46	0.68	0.00	0.78	0.89
2014	1.38	1.42	0.69	0.01	0.72	0.87
2015	1.34	1.38	0.61	0.00	0.70	0.86
2016	1.38	1.42	0.60	0.00	0.69	0.84
2017	1.34	1.46	0.63	0.00	0.72	0.89
2018	1.46	1.50	0.68	0.01	0.75	0.88
2019	1.38	1.46	0.60	0.00	0.70	0.85

# Primero infraestimando ($L_{inf}^{LIT}$ multiplicado por 0.75):


lb_tableSH(freq, 1, "mm", linf=0.75*86.0, lmat=25.0, mk_ratio=1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.22	1.30	0.76	0.10	0.94	0.99
1983	1.06	1.18	0.74	0.06	0.87	1.00
1984	1.14	1.22	0.76	0.09	0.89	0.98
1985	1.14	1.22	0.76	0.10	0.91	0.99
1986	1.22	1.26	0.73	0.07	0.93	0.97
1987	1.26	1.26	0.76	0.13	0.96	0.99
1988	1.30	1.34	0.75	0.10	0.97	0.97
1989	1.34	1.42	0.83	0.27	1.04	1.02
1990	1.22	1.30	0.79	0.11	0.94	0.99
1991	1.10	1.22	0.72	0.06	0.87	0.97
1992	1.26	1.30	0.75	0.10	0.95	0.98
1993	1.26	1.30	0.77	0.14	0.96	0.99
1994	1.18	1.26	0.77	0.09	0.93	1.00
1995	1.18	1.30	0.74	0.10	0.93	1.00
1996	1.22	1.30	0.80	0.11	0.94	0.99
1997	1.18	1.30	0.73	0.07	0.91	0.98
1998	1.34	1.38	0.80	0.20	1.01	1.00
1999	1.18	1.26	0.79	0.13	0.94	1.00
2000	1.26	1.34	0.83	0.13	0.96	0.99
2001	1.26	1.30	0.78	0.11	0.95	0.98
2002	1.26	1.34	0.87	0.20	0.98	1.01
2003	1.38	1.46	0.94	0.35	1.08	1.05
2004	1.26	1.38	0.96	0.28	1.05	1.08
2005	1.26	1.34	0.92	0.19	1.00	1.03
2006	1.30	1.38	1.01	0.24	1.04	1.05
2007	1.30	1.42	0.85	0.26	1.02	1.03
2008	1.42	1.50	0.97	0.41	1.12	1.07
2009	1.50	1.62	1.11	0.64	1.25	1.14
2010	1.34	1.46	0.95	0.43	1.10	1.09
2011	1.50	1.58	0.96	0.37	1.11	1.02
2012	1.58	1.58	0.89	0.50	1.17	1.03
2013	1.54	1.46	0.90	0.37	1.13	1.02
2014	1.38	1.42	0.92	0.25	1.04	1.01
2015	1.34	1.38	0.81	0.23	1.01	1.00
2016	1.38	1.42	0.81	0.17	1.00	0.97
2017	1.34	1.46	0.84	0.32	1.05	1.04
2018	1.46	1.50	0.90	0.34	1.09	1.02
2019	1.38	1.46	0.80	0.21	1.02	0.99

# Segundo sobrestimando ($L_{inf}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 1, "mm", linf=1.25*86.0, lmat=25.0, mk_ratio=1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.22	1.30	0.46	0.00	0.56	0.80
1983	1.06	1.18	0.44	0.00	0.52	0.80
1984	1.14	1.22	0.46	0.00	0.54	0.79
1985	1.14	1.22	0.46	0.00	0.54	0.80
1986	1.22	1.26	0.44	0.00	0.56	0.79
1987	1.26	1.26	0.46	0.00	0.58	0.80
1988	1.30	1.34	0.45	0.00	0.58	0.79
1989	1.34	1.42	0.50	0.00	0.62	0.84
1990	1.22	1.30	0.47	0.00	0.56	0.80
1991	1.10	1.22	0.43	0.00	0.52	0.78
1992	1.26	1.30	0.45	0.00	0.57	0.79
1993	1.26	1.30	0.46	0.00	0.58	0.81
1994	1.18	1.26	0.46	0.00	0.56	0.80
1995	1.18	1.30	0.44	0.00	0.56	0.80
1996	1.22	1.30	0.48	0.00	0.57	0.80
1997	1.18	1.30	0.44	0.00	0.55	0.79
1998	1.34	1.38	0.48	0.00	0.61	0.82
1999	1.18	1.26	0.47	0.00	0.56	0.81
2000	1.26	1.34	0.50	0.00	0.57	0.80
2001	1.26	1.30	0.47	0.00	0.57	0.79
2002	1.26	1.34	0.52	0.00	0.59	0.82
2003	1.38	1.46	0.56	0.00	0.65	0.86
2004	1.26	1.38	0.58	0.00	0.63	0.87
2005	1.26	1.34	0.55	0.00	0.60	0.84
2006	1.30	1.38	0.60	0.00	0.63	0.86
2007	1.30	1.42	0.51	0.00	0.61	0.84
2008	1.42	1.50	0.58	0.00	0.67	0.88
2009	1.50	1.62	0.67	0.02	0.75	0.95
2010	1.34	1.46	0.57	0.00	0.66	0.89
2011	1.50	1.58	0.58	0.00	0.67	0.84
2012	1.58	1.58	0.53	0.00	0.70	0.86
2013	1.54	1.46	0.54	0.00	0.68	0.84
2014	1.38	1.42	0.55	0.00	0.62	0.83
2015	1.34	1.38	0.49	0.00	0.61	0.82
2016	1.38	1.42	0.48	0.00	0.60	0.80
2017	1.34	1.46	0.50	0.00	0.63	0.85
2018	1.46	1.50	0.54	0.00	0.66	0.84
2019	1.38	1.46	0.48	0.00	0.61	0.81

Norway Loster 8c FU25 Females

La cigala FU 25 females. Los datos del ciclo vital recogidos de la literatura son:

\(L_{mat}^{LIT}\) = 28.0 mm. Females (Fariña, 1996). Creo que tesis Celso.

\(L_{inf}^{LIT}\) = 71.0 mm. Females (Distribución de tallas, 2010).

\({M/k}^{LIT}\) = 1.9 (Prince, 2015).

wal <- read.csv("25_Females_w.csv", stringsAsFactors = FALSE)
freq <- read.csv("25_Females.csv",  stringsAsFactors = FALSE)
head(wal)

##   MeanLength    X1982    X1983    X1984    X1985    X1986    X1987    X1988
## 1         15 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000
## 2         16 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000
## 3         17 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000
## 4         18 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000
## 5         19 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518
## 6         20 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757
##      X1989    X1990    X1991    X1992    X1993    X1994    X1995    X1996
## 1 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000
## 2 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000
## 3 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000
## 4 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000
## 5 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518
## 6 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757
##      X1997    X1998    X1999    X2000    X2001    X2002    X2003    X2004
## 1 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000
## 2 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000
## 3 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000
## 4 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000
## 5 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518
## 6 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757
##      X2005    X2006    X2007    X2008    X2009    X2010    X2011    X2012
## 1 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000
## 2 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000
## 3 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000
## 4 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000
## 5 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518
## 6 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757
##      X2013    X2014    X2015    X2016    X2017    X2018    X2019
## 1 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000 2.500000
## 2 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000 3.000000
## 3 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000 3.600000
## 4 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000 4.300000
## 5 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518 5.069518
## 6 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757 5.936757

head(freq)

##   MeanLength X1982 X1983 X1984 X1985 X1986 X1987 X1988 X1989 X1990 X1991 X1992
## 1         15    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 2         16    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 3         17    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 4         18    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5         19   791    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 6         20     0 13378    NA    NA   782    NA    NA    NA  2494    NA    NA
##   X1993 X1994 X1995 X1996 X1997 X1998 X1999 X2000 X2001 X2002 X2003 X2004 X2005
## 1    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 2    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 3    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 6    NA    NA    NA   925    NA    NA    NA    NA    NA    NA    NA    NA    NA
##   X2006 X2007 X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015 X2016 X2017 X2018
## 1    NA    NA    NA    NA    NA    NA    NA  6044    NA    NA    NA    NA    NA
## 2    NA    NA    NA    NA    NA    NA    NA     0    NA    NA    NA    NA    NA
## 3    NA    NA    NA    NA    NA    NA    NA     0    NA    NA    NA    NA    NA
## 4    NA    NA    NA    NA    NA    NA    NA     0    NA    NA    NA    NA    NA
## 5    NA    NA    NA    NA    NA    NA    NA     0    NA    NA    NA    NA    NA
## 6    NA    77    NA    NA    NA    NA    NA   223    NA    NA    NA    NA    NA
##   X2019
## 1    NA
## 2    NA
## 3    NA
## 4    NA
## 5    NA
## 6    NA

bin_plot(freq, 1, "cm")

lb_tableSH(freq, 1, "mm", linf = 71.0 , lmat = 28.0 , mk_ratio = 1.90 ,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.05	1.09	0.66	0.01	0.81	0.93
1983	0.88	0.98	0.60	0.00	0.73	0.93
1984	1.02	1.02	0.61	0.00	0.76	0.88
1985	0.95	1.02	0.63	0.01	0.74	0.90
1986	0.98	1.05	0.64	0.01	0.78	0.93
1987	0.95	1.09	0.67	0.01	0.80	0.98
1988	1.05	1.12	0.67	0.01	0.82	0.93
1989	1.20	1.23	0.68	0.02	0.89	0.93
1990	1.05	1.12	0.67	0.02	0.84	0.96
1991	0.98	1.05	0.65	0.01	0.76	0.91
1992	1.05	1.12	0.61	0.00	0.80	0.91
1993	1.16	1.16	0.63	0.00	0.84	0.90
1994	0.98	1.09	0.61	0.00	0.79	0.94
1995	1.05	1.12	0.63	0.00	0.82	0.93
1996	1.05	1.09	0.66	0.01	0.81	0.92
1997	1.05	1.09	0.64	0.01	0.80	0.92
1998	1.05	1.20	0.67	0.02	0.85	0.97
1999	1.05	1.16	0.67	0.02	0.84	0.95
2000	1.12	1.16	0.66	0.01	0.84	0.92
2001	1.02	1.12	0.65	0.01	0.81	0.94
2002	1.12	1.20	0.66	0.02	0.85	0.93
2003	1.27	1.27	0.71	0.04	0.91	0.92
2004	1.12	1.16	0.70	0.03	0.87	0.95
2005	1.09	1.16	0.70	0.03	0.86	0.96
2006	1.09	1.16	0.71	0.04	0.86	0.96
2007	1.16	1.23	0.70	0.03	0.89	0.95
2008	1.23	1.27	0.74	0.08	0.94	0.97
2009	1.30	1.41	0.83	0.24	1.04	1.03
2010	1.16	1.23	0.79	0.13	0.94	1.01
2011	1.34	1.34	0.85	0.14	0.98	0.96
2012	1.23	1.23	0.82	0.12	0.96	0.99
2013	0.77	0.91	0.67	0.02	0.78	1.06
2014	1.20	1.23	0.77	0.08	0.91	0.96
2015	1.05	1.16	0.73	0.05	0.86	0.99
2016	1.23	1.23	0.68	0.02	0.87	0.90
2017	1.20	1.27	0.72	0.04	0.90	0.94
2018	1.27	1.30	0.73	0.05	0.94	0.96
2019	1.20	1.27	0.71	0.04	0.89	0.94

#Primero infraestimando (${M/k}^{LIT}$ multiplicado por 0.75):

lb_tableSH(freq, 1, "mm", linf=71.0, lmat=28.0, mk_ratio=0.75*1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.05	1.09	0.66	0.00	0.73	0.88
1983	0.88	0.98	0.60	0.00	0.66	0.87
1984	1.02	1.02	0.61	0.00	0.69	0.84
1985	0.95	1.02	0.63	0.00	0.67	0.85
1986	0.98	1.05	0.64	0.00	0.70	0.87
1987	0.95	1.09	0.67	0.00	0.73	0.92
1988	1.05	1.12	0.67	0.00	0.74	0.88
1989	1.20	1.23	0.68	0.00	0.80	0.89
1990	1.05	1.12	0.67	0.00	0.76	0.91
1991	0.98	1.05	0.65	0.00	0.69	0.86
1992	1.05	1.12	0.61	0.00	0.72	0.86
1993	1.16	1.16	0.63	0.00	0.76	0.86
1994	0.98	1.09	0.61	0.00	0.71	0.88
1995	1.05	1.12	0.63	0.00	0.74	0.88
1996	1.05	1.09	0.66	0.00	0.73	0.87
1997	1.05	1.09	0.64	0.00	0.73	0.87
1998	1.05	1.20	0.67	0.00	0.77	0.92
1999	1.05	1.16	0.67	0.00	0.75	0.90
2000	1.12	1.16	0.66	0.00	0.76	0.88
2001	1.02	1.12	0.65	0.00	0.73	0.89
2002	1.12	1.20	0.66	0.00	0.76	0.88
2003	1.27	1.27	0.71	0.01	0.82	0.89
2004	1.12	1.16	0.70	0.01	0.79	0.91
2005	1.09	1.16	0.70	0.01	0.78	0.91
2006	1.09	1.16	0.71	0.01	0.78	0.91
2007	1.16	1.23	0.70	0.01	0.80	0.91
2008	1.23	1.27	0.74	0.02	0.85	0.93
2009	1.30	1.41	0.83	0.10	0.94	0.99
2010	1.16	1.23	0.79	0.04	0.85	0.96
2011	1.34	1.34	0.85	0.08	0.89	0.92
2012	1.23	1.23	0.82	0.06	0.87	0.95
2013	0.77	0.91	0.67	0.00	0.70	0.98
2014	1.20	1.23	0.77	0.03	0.82	0.92
2015	1.05	1.16	0.73	0.02	0.78	0.93
2016	1.23	1.23	0.68	0.01	0.79	0.86
2017	1.20	1.27	0.72	0.01	0.81	0.90
2018	1.27	1.30	0.73	0.01	0.85	0.92
2019	1.20	1.27	0.71	0.00	0.81	0.90

# Segundo sobrestimando (${M/k}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 1, "mm", linf=71.0, lmat=28.0, mk_ratio=1.25*1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.05	1.09	0.66	0.04	0.89	0.96
1983	0.88	0.98	0.60	0.01	0.80	0.97
1984	1.02	1.02	0.61	0.02	0.83	0.92
1985	0.95	1.02	0.63	0.02	0.82	0.95
1986	0.98	1.05	0.64	0.02	0.86	0.97
1987	0.95	1.09	0.67	0.07	0.88	1.02
1988	1.05	1.12	0.67	0.07	0.90	0.97
1989	1.20	1.23	0.68	0.08	0.97	0.96
1990	1.05	1.12	0.67	0.08	0.93	1.00
1991	0.98	1.05	0.65	0.04	0.84	0.95
1992	1.05	1.12	0.61	0.01	0.87	0.94
1993	1.16	1.16	0.63	0.03	0.92	0.93
1994	0.98	1.09	0.61	0.02	0.86	0.98
1995	1.05	1.12	0.63	0.02	0.90	0.97
1996	1.05	1.09	0.66	0.04	0.88	0.95
1997	1.05	1.09	0.64	0.03	0.88	0.95
1998	1.05	1.20	0.67	0.08	0.93	1.01
1999	1.05	1.16	0.67	0.06	0.92	0.99
2000	1.12	1.16	0.66	0.05	0.93	0.96
2001	1.02	1.12	0.65	0.04	0.89	0.98
2002	1.12	1.20	0.66	0.06	0.93	0.96
2003	1.27	1.27	0.71	0.10	1.00	0.95
2004	1.12	1.16	0.70	0.09	0.96	0.99
2005	1.09	1.16	0.70	0.09	0.94	1.00
2006	1.09	1.16	0.71	0.10	0.94	1.00
2007	1.16	1.23	0.70	0.10	0.97	0.98
2008	1.23	1.27	0.74	0.19	1.03	1.00
2009	1.30	1.41	0.83	0.48	1.14	1.06
2010	1.16	1.23	0.79	0.26	1.03	1.04
2011	1.34	1.34	0.85	0.18	1.08	0.98
2012	1.23	1.23	0.82	0.20	1.05	1.02
2013	0.77	0.91	0.67	0.09	0.85	1.12
2014	1.20	1.23	0.77	0.16	1.00	0.99
2015	1.05	1.16	0.73	0.12	0.95	1.02
2016	1.23	1.23	0.68	0.05	0.96	0.93
2017	1.20	1.27	0.72	0.09	0.98	0.98
2018	1.27	1.30	0.73	0.18	1.04	0.99
2019	1.20	1.27	0.71	0.11	0.98	0.97

# Tercero usando el valor por defecto de 1.5.

lb_tableSH(freq, 1, "m", linf=71.0, lmat=28.0, mk_ratio=1.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.05	1.09	0.66	0.00	0.75	0.89
1983	0.88	0.98	0.60	0.00	0.67	0.88
1984	1.02	1.02	0.61	0.00	0.70	0.84
1985	0.95	1.02	0.63	0.00	0.68	0.86
1986	0.98	1.05	0.64	0.00	0.72	0.88
1987	0.95	1.09	0.67	0.01	0.74	0.93
1988	1.05	1.12	0.67	0.00	0.75	0.89
1989	1.20	1.23	0.68	0.00	0.81	0.90
1990	1.05	1.12	0.67	0.00	0.77	0.92
1991	0.98	1.05	0.65	0.00	0.70	0.87
1992	1.05	1.12	0.61	0.00	0.73	0.87
1993	1.16	1.16	0.63	0.00	0.77	0.87
1994	0.98	1.09	0.61	0.00	0.72	0.89
1995	1.05	1.12	0.63	0.00	0.75	0.89
1996	1.05	1.09	0.66	0.00	0.74	0.88
1997	1.05	1.09	0.64	0.00	0.74	0.88
1998	1.05	1.20	0.67	0.00	0.78	0.93
1999	1.05	1.16	0.67	0.00	0.77	0.91
2000	1.12	1.16	0.66	0.00	0.77	0.89
2001	1.02	1.12	0.65	0.00	0.74	0.90
2002	1.12	1.20	0.66	0.00	0.78	0.89
2003	1.27	1.27	0.71	0.01	0.84	0.89
2004	1.12	1.16	0.70	0.01	0.80	0.92
2005	1.09	1.16	0.70	0.01	0.79	0.92
2006	1.09	1.16	0.71	0.01	0.79	0.92
2007	1.16	1.23	0.70	0.01	0.81	0.92
2008	1.23	1.27	0.74	0.02	0.86	0.94
2009	1.30	1.41	0.83	0.13	0.95	1.00
2010	1.16	1.23	0.79	0.06	0.86	0.97
2011	1.34	1.34	0.85	0.09	0.90	0.93
2012	1.23	1.23	0.82	0.07	0.88	0.96
2013	0.77	0.91	0.67	0.00	0.71	1.00
2014	1.20	1.23	0.77	0.04	0.84	0.93
2015	1.05	1.16	0.73	0.02	0.79	0.94
2016	1.23	1.23	0.68	0.01	0.80	0.87
2017	1.20	1.27	0.72	0.02	0.82	0.91
2018	1.27	1.30	0.73	0.02	0.87	0.93
2019	1.20	1.27	0.71	0.01	0.82	0.91

# Primero infraestimando ($L_{inf}^{LIT}$ multiplicado por 0.75):

lb_tableSH(freq, 1, "mm", linf=0.75*71.0, lmat=28.0, mk_ratio=1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.05	1.09	0.87	0.31	1.08	1.02
1983	0.88	0.98	0.80	0.17	0.97	1.04
1984	1.02	1.02	0.82	0.15	1.01	0.98
1985	0.95	1.02	0.84	0.17	0.99	1.01
1986	0.98	1.05	0.85	0.25	1.04	1.03
1987	0.95	1.09	0.90	0.33	1.07	1.09
1988	1.05	1.12	0.89	0.35	1.09	1.03
1989	1.20	1.23	0.91	0.62	1.18	1.02
1990	1.05	1.12	0.90	0.44	1.12	1.06
1991	0.98	1.05	0.86	0.22	1.02	1.01
1992	1.05	1.12	0.82	0.29	1.06	1.00
1993	1.16	1.16	0.84	0.40	1.12	0.99
1994	0.98	1.09	0.82	0.29	1.05	1.04
1995	1.05	1.12	0.84	0.35	1.09	1.03
1996	1.05	1.09	0.88	0.28	1.07	1.02
1997	1.05	1.09	0.86	0.29	1.07	1.01
1998	1.05	1.20	0.90	0.52	1.13	1.07
1999	1.05	1.16	0.89	0.45	1.11	1.05
2000	1.12	1.16	0.87	0.41	1.12	1.02
2001	1.02	1.12	0.86	0.37	1.08	1.05
2002	1.12	1.20	0.89	0.44	1.13	1.02
2003	1.27	1.27	0.95	0.67	1.22	1.01
2004	1.12	1.16	0.94	0.51	1.16	1.05
2005	1.09	1.16	0.93	0.49	1.15	1.06
2006	1.09	1.16	0.95	0.49	1.15	1.06
2007	1.16	1.23	0.93	0.59	1.18	1.05
2008	1.23	1.27	0.99	0.73	1.25	1.06
2009	1.30	1.41	1.11	0.92	1.38	1.13
2010	1.16	1.23	1.05	0.63	1.25	1.11
2011	1.34	1.34	1.14	0.79	1.31	1.05
2012	1.23	1.23	1.10	0.64	1.28	1.09
2013	0.77	0.91	0.90	0.35	1.03	1.20
2014	1.20	1.23	1.02	0.63	1.22	1.06
2015	1.05	1.16	0.98	0.52	1.15	1.09
2016	1.23	1.23	0.91	0.51	1.16	0.99
2017	1.20	1.27	0.96	0.66	1.20	1.04
2018	1.27	1.30	0.97	0.80	1.26	1.05
2019	1.20	1.27	0.94	0.66	1.19	1.03

# Segundo sobrestimando ($L_{inf}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 1, "mm", linf=1.25*71.0, lmat=28.0, mk_ratio=1.9,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1982	1.05	1.09	0.52	0.00	0.65	0.84
1983	0.88	0.98	0.48	0.00	0.58	0.84
1984	1.02	1.02	0.49	0.00	0.61	0.80
1985	0.95	1.02	0.51	0.00	0.60	0.82
1986	0.98	1.05	0.51	0.00	0.62	0.84
1987	0.95	1.09	0.54	0.00	0.64	0.89
1988	1.05	1.12	0.54	0.00	0.66	0.85
1989	1.20	1.23	0.55	0.00	0.71	0.86
1990	1.05	1.12	0.54	0.00	0.67	0.88
1991	0.98	1.05	0.52	0.00	0.61	0.83
1992	1.05	1.12	0.49	0.00	0.64	0.83
1993	1.16	1.16	0.50	0.00	0.67	0.83
1994	0.98	1.09	0.49	0.00	0.63	0.85
1995	1.05	1.12	0.50	0.00	0.65	0.85
1996	1.05	1.09	0.53	0.00	0.64	0.84
1997	1.05	1.09	0.52	0.00	0.64	0.83
1998	1.05	1.20	0.54	0.00	0.68	0.88
1999	1.05	1.16	0.53	0.00	0.67	0.87
2000	1.12	1.16	0.52	0.00	0.67	0.84
2001	1.02	1.12	0.52	0.00	0.65	0.86
2002	1.12	1.20	0.53	0.00	0.68	0.85
2003	1.27	1.27	0.57	0.00	0.73	0.85
2004	1.12	1.16	0.56	0.00	0.70	0.87
2005	1.09	1.16	0.56	0.00	0.69	0.88
2006	1.09	1.16	0.57	0.00	0.69	0.88
2007	1.16	1.23	0.56	0.00	0.71	0.87
2008	1.23	1.27	0.60	0.00	0.75	0.89
2009	1.30	1.41	0.66	0.01	0.83	0.95
2010	1.16	1.23	0.63	0.01	0.75	0.92
2011	1.34	1.34	0.68	0.03	0.79	0.89
2012	1.23	1.23	0.66	0.03	0.77	0.91
2013	0.77	0.91	0.54	0.00	0.62	0.95
2014	1.20	1.23	0.61	0.01	0.73	0.88
2015	1.05	1.16	0.59	0.00	0.69	0.90
2016	1.23	1.23	0.55	0.00	0.70	0.83
2017	1.20	1.27	0.58	0.00	0.72	0.87
2018	1.27	1.30	0.58	0.00	0.76	0.88
2019	1.20	1.27	0.57	0.00	0.72	0.86

Norway Loster FU2627

Norway Loster FU2627 Males

Los datos del ciclo vital de Nephrops FU2627 recogidos de la literatura son:

\(L_{mat}^{LIT}\) = 28 mm. Males in FU29 (ICES, 2006).

\(L_{inf}^{LIT}\) = 80 mm. Males FU2627 (Fernández, et al., 1986).

\({M/k}^{LIT}\) =0.2/0150=2 (k 0.150 year-1 y M=0.2 (Fernández, et al., 1986 & Morizur,Y. 1982).

wal <- read.csv("FU2627_PesosMales_1988_2019_medio.csv", stringsAsFactors = FALSE)
freq <- read.csv("FU2627_tallasMales_1988_2019.csv", stringsAsFactors = FALSE)
head(freq)

##   talla X1988  X1989  X1990 X1991 X1992 X1993 X1994 X1995 X1996 X1997 X1998
## 1    12     0      0   7594     0     0     0     0     0     0     0     0
## 2    13     0  66181   8178     0     0     0     0     0     0     0     0
## 3    14     0  66181  10497     0     0     0     0     0     0     0     0
## 4    15     0 339166  84532     0     0     0     0     0     0     0     0
## 5    16     0  75996 135341  5393     0     0     0     0     0     0     0
## 6    17     0  92508 175731  8053     0     0  5015     0     0     0     0
##   X1999 X2000 X2001 X2002 X2003 X2004 X2005 X2006 X2007 X2008 X2009 X2010 X2011
## 1     0     0     0     0     0     0     0     0     0     0     0     0     0
## 2     0     0     0     0     0     0     0     0     0     0     0     0     0
## 3     0     0     0     0     0     0     0     0     0     0     0     0     0
## 4     0     0     0     0     0     0     0     0     0     0     0     0     0
## 5     0     0  4030     0     0     0     0     0     0     0     0     0     0
## 6     0     0   232   142     0     0     0     0     0     0     0     0     0
##   X2012 X2013 X2014 X2015 X2016 X2017 X2018 X2019
## 1     0     0     0     0     0     0     0     0
## 2     0     0     0     0     0     0     0     0
## 3     0     0     0     0     0     0     0     0
## 4     0     0     0     0     0     0     0     0
## 5     0     0     0     0     0     0     0     0
## 6     0     0     0     0     0     0     0     0

head(wal)

##   talla    X1988    X1989    X1990    X1991    X1992    X1993    X1994    X1995
## 1    12 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068
## 2    13 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439
## 3    14 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904
## 4    15 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656
## 5    16 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947
## 6    17 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080
##      X1996    X1997    X1998    X1999    X2000    X2001    X2002    X2003
## 1 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068
## 2 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439
## 3 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904
## 4 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656
## 5 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947
## 6 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080
##      X2004    X2005    X2006    X2007    X2008    X2009    X2010    X2011
## 1 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068
## 2 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439
## 3 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904
## 4 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656
## 5 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947
## 6 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080
##      X2012    X2013    X2014    X2015    X2016    X2017    X2018    X2019  X
## 1 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 NA
## 2 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 NA
## 3 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 NA
## 4 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 NA
## 5 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 NA
## 6 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 NA
##   X.1 X.2
## 1  NA  NA
## 2  NA  NA
## 3  NA  NA
## 4  NA  NA
## 5  NA  NA
## 6  NA  NA

bin_plot(freq, 1, "cm")

lb_tableSH(freq, 2, "mm", linf=80, lmat=28, mk_ratio=2,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.11	0.60	0.01	0.73	0.89
1989	0.75	0.82	0.61	0.01	0.63	0.92
1990	0.68	0.75	0.52	0.00	0.53	0.82
1991	0.82	0.96	0.57	0.00	0.65	0.90
1992	0.96	1.04	0.64	0.01	0.75	0.96
1993	0.96	1.04	0.62	0.01	0.71	0.91
1994	1.04	1.11	0.67	0.02	0.76	0.93
1995	0.96	1.04	0.57	0.00	0.69	0.88
1996	0.89	0.89	0.60	0.01	0.66	0.89
1997	0.96	1.11	0.63	0.02	0.75	0.96
1998	1.11	1.18	0.66	0.02	0.80	0.94
1999	1.11	1.18	0.65	0.02	0.79	0.93
2000	0.75	0.96	0.72	0.03	0.72	1.05
2001	0.82	0.82	0.63	0.02	0.63	0.88
2002	1.11	1.11	0.74	0.05	0.82	0.97
2003	1.04	1.11	0.78	0.07	0.83	1.01
2004	1.18	1.25	0.78	0.07	0.87	0.99
2005	1.04	1.25	0.86	0.15	0.89	1.09
2006	1.18	1.25	0.83	0.10	0.88	1.00
2007	1.18	1.32	0.80	0.10	0.89	1.01
2008	1.11	1.25	0.83	0.17	0.91	1.07
2009	1.11	1.32	0.86	0.27	0.95	1.11
2010	1.32	1.54	0.90	0.45	1.08	1.14
2011	1.39	1.39	0.90	0.28	1.04	1.06
2012	1.32	1.46	0.90	0.26	1.03	1.09
2013	1.11	1.25	0.88	0.37	0.99	1.17
2014	1.39	1.39	0.86	0.30	1.06	1.07
2015	1.25	1.32	0.87	0.21	0.94	1.03
2016	1.25	1.39	0.84	0.27	0.98	1.07
2017	1.39	1.46	0.88	0.36	1.06	1.07
2018	1.04	1.39	0.85	0.34	0.99	1.21
2019	1.18	1.39	0.84	0.26	0.97	1.10

# Primero infraestimando (${M/k}^{LIT}$ multiplicado por 0.75):
lb_tableSH(freq, 2, "mm", linf=80, lmat=28, mk_ratio=0.75*2,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.11	0.60	0.00	0.65	0.84
1989	0.75	0.82	0.61	0.00	0.56	0.84
1990	0.68	0.75	0.52	0.00	0.48	0.74
1991	0.82	0.96	0.57	0.00	0.58	0.83
1992	0.96	1.04	0.64	0.00	0.68	0.90
1993	0.96	1.04	0.62	0.00	0.64	0.85
1994	1.04	1.11	0.67	0.01	0.68	0.87
1995	0.96	1.04	0.57	0.00	0.62	0.82
1996	0.89	0.89	0.60	0.00	0.60	0.82
1997	0.96	1.11	0.63	0.00	0.68	0.90
1998	1.11	1.18	0.66	0.00	0.72	0.89
1999	1.11	1.18	0.65	0.00	0.71	0.88
2000	0.75	0.96	0.72	0.02	0.64	0.96
2001	0.82	0.82	0.63	0.01	0.57	0.82
2002	1.11	1.11	0.74	0.03	0.74	0.91
2003	1.04	1.11	0.78	0.03	0.74	0.95
2004	1.18	1.25	0.78	0.04	0.79	0.94
2005	1.04	1.25	0.86	0.08	0.80	1.03
2006	1.18	1.25	0.83	0.05	0.79	0.94
2007	1.18	1.32	0.80	0.04	0.81	0.96
2008	1.11	1.25	0.83	0.07	0.82	1.01
2009	1.11	1.32	0.86	0.13	0.85	1.05
2010	1.32	1.54	0.90	0.22	0.97	1.09
2011	1.39	1.39	0.90	0.16	0.93	1.01
2012	1.32	1.46	0.90	0.17	0.93	1.04
2013	1.11	1.25	0.88	0.30	0.89	1.10
2014	1.39	1.39	0.86	0.19	0.95	1.03
2015	1.25	1.32	0.87	0.10	0.85	0.98
2016	1.25	1.39	0.84	0.14	0.88	1.02
2017	1.39	1.46	0.88	0.20	0.95	1.03
2018	1.04	1.39	0.85	0.23	0.89	1.13
2019	1.18	1.39	0.84	0.13	0.87	1.04

# Segundo sobrestimando (${M/k}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 2, "mm", linf=80, lmat=28, mk_ratio=1.25*2,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.11	0.60	0.02	0.80	0.93
1989	0.75	0.82	0.61	0.02	0.69	0.98
1990	0.68	0.75	0.52	0.00	0.58	0.87
1991	0.82	0.96	0.57	0.01	0.71	0.95
1992	0.96	1.04	0.64	0.04	0.83	1.01
1993	0.96	1.04	0.62	0.03	0.78	0.95
1994	1.04	1.11	0.67	0.05	0.83	0.97
1995	0.96	1.04	0.57	0.01	0.76	0.93
1996	0.89	0.89	0.60	0.02	0.73	0.93
1997	0.96	1.11	0.63	0.04	0.83	1.01
1998	1.11	1.18	0.66	0.08	0.88	0.98
1999	1.11	1.18	0.65	0.06	0.87	0.97
2000	0.75	0.96	0.72	0.06	0.79	1.11
2001	0.82	0.82	0.63	0.02	0.70	0.94
2002	1.11	1.11	0.74	0.09	0.90	1.01
2003	1.04	1.11	0.78	0.13	0.91	1.06
2004	1.18	1.25	0.78	0.12	0.96	1.03
2005	1.04	1.25	0.86	0.25	0.98	1.14
2006	1.18	1.25	0.83	0.16	0.97	1.03
2007	1.18	1.32	0.80	0.18	0.98	1.05
2008	1.11	1.25	0.83	0.26	1.00	1.12
2009	1.11	1.32	0.86	0.37	1.04	1.16
2010	1.32	1.54	0.90	0.59	1.19	1.18
2011	1.39	1.39	0.90	0.42	1.14	1.09
2012	1.32	1.46	0.90	0.44	1.14	1.12
2013	1.11	1.25	0.88	0.41	1.09	1.22
2014	1.39	1.39	0.86	0.46	1.16	1.11
2015	1.25	1.32	0.87	0.28	1.04	1.06
2016	1.25	1.39	0.84	0.39	1.08	1.11
2017	1.39	1.46	0.88	0.46	1.16	1.11
2018	1.04	1.39	0.85	0.43	1.09	1.26
2019	1.18	1.39	0.84	0.38	1.07	1.14

# Tercero usando el valor por defecto de 1.5.

lb_tableSH(freq, 2, "mm", linf=80, lmat=28, mk_ratio=1.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.11	0.60	0.00	0.65	0.84
1989	0.75	0.82	0.61	0.00	0.56	0.84
1990	0.68	0.75	0.52	0.00	0.48	0.74
1991	0.82	0.96	0.57	0.00	0.58	0.83
1992	0.96	1.04	0.64	0.00	0.68	0.90
1993	0.96	1.04	0.62	0.00	0.64	0.85
1994	1.04	1.11	0.67	0.01	0.68	0.87
1995	0.96	1.04	0.57	0.00	0.62	0.82
1996	0.89	0.89	0.60	0.00	0.60	0.82
1997	0.96	1.11	0.63	0.00	0.68	0.90
1998	1.11	1.18	0.66	0.00	0.72	0.89
1999	1.11	1.18	0.65	0.00	0.71	0.88
2000	0.75	0.96	0.72	0.02	0.64	0.96
2001	0.82	0.82	0.63	0.01	0.57	0.82
2002	1.11	1.11	0.74	0.03	0.74	0.91
2003	1.04	1.11	0.78	0.03	0.74	0.95
2004	1.18	1.25	0.78	0.04	0.79	0.94
2005	1.04	1.25	0.86	0.08	0.80	1.03
2006	1.18	1.25	0.83	0.05	0.79	0.94
2007	1.18	1.32	0.80	0.04	0.81	0.96
2008	1.11	1.25	0.83	0.07	0.82	1.01
2009	1.11	1.32	0.86	0.13	0.85	1.05
2010	1.32	1.54	0.90	0.22	0.97	1.09
2011	1.39	1.39	0.90	0.16	0.93	1.01
2012	1.32	1.46	0.90	0.17	0.93	1.04
2013	1.11	1.25	0.88	0.30	0.89	1.10
2014	1.39	1.39	0.86	0.19	0.95	1.03
2015	1.25	1.32	0.87	0.10	0.85	0.98
2016	1.25	1.39	0.84	0.14	0.88	1.02
2017	1.39	1.46	0.88	0.20	0.95	1.03
2018	1.04	1.39	0.85	0.23	0.89	1.13
2019	1.18	1.39	0.84	0.13	0.87	1.04

# Primero infraestimando ($L_{inf}^{LIT}$ multiplicado por 0.75):

lb_tableSH(freq, 2, "mm", linf=0.75*80, lmat=28, mk_ratio=2,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.11	0.80	0.12	0.97	0.99
1989	0.75	0.82	0.81	0.10	0.84	1.04
1990	0.68	0.75	0.69	0.02	0.71	0.94
1991	0.82	0.96	0.76	0.07	0.86	1.02
1992	0.96	1.04	0.85	0.25	1.00	1.08
1993	0.96	1.04	0.82	0.14	0.95	1.01
1994	1.04	1.11	0.90	0.21	1.01	1.03
1995	0.96	1.04	0.76	0.09	0.92	0.99
1996	0.89	0.89	0.80	0.10	0.89	1.00
1997	0.96	1.11	0.84	0.26	1.00	1.07
1998	1.11	1.18	0.88	0.31	1.07	1.05
1999	1.11	1.18	0.87	0.29	1.06	1.04
2000	0.75	0.96	0.96	0.20	0.95	1.19
2001	0.82	0.82	0.84	0.09	0.85	1.00
2002	1.11	1.11	0.99	0.33	1.09	1.07
2003	1.04	1.11	1.04	0.36	1.10	1.13
2004	1.18	1.25	1.04	0.49	1.17	1.09
2005	1.04	1.25	1.14	0.52	1.19	1.22
2006	1.18	1.25	1.11	0.46	1.17	1.10
2007	1.18	1.32	1.06	0.59	1.19	1.12
2008	1.11	1.25	1.10	0.57	1.22	1.19
2009	1.11	1.32	1.15	0.61	1.26	1.23
2010	1.32	1.54	1.20	0.84	1.44	1.25
2011	1.39	1.39	1.20	0.74	1.38	1.15
2012	1.32	1.46	1.20	0.79	1.38	1.19
2013	1.11	1.25	1.17	0.57	1.32	1.30
2014	1.39	1.39	1.15	0.72	1.41	1.17
2015	1.25	1.32	1.15	0.57	1.26	1.13
2016	1.25	1.39	1.12	0.67	1.30	1.17
2017	1.39	1.46	1.17	0.75	1.41	1.17
2018	1.04	1.39	1.13	0.67	1.32	1.35
2019	1.18	1.39	1.12	0.71	1.29	1.21

# Segundo sobrestimando ($L_{inf}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 2, "mm", linf=1.25*80, lmat=28, mk_ratio=2,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.11	0.48	0.00	0.58	0.81
1989	0.75	0.82	0.49	0.00	0.50	0.82
1990	0.68	0.75	0.41	0.00	0.42	0.72
1991	0.82	0.96	0.46	0.00	0.52	0.81
1992	0.96	1.04	0.51	0.00	0.60	0.87
1993	0.96	1.04	0.49	0.00	0.57	0.82
1994	1.04	1.11	0.54	0.00	0.61	0.84
1995	0.96	1.04	0.46	0.00	0.55	0.80
1996	0.89	0.89	0.48	0.00	0.53	0.80
1997	0.96	1.11	0.51	0.00	0.60	0.87
1998	1.11	1.18	0.53	0.00	0.64	0.86
1999	1.11	1.18	0.52	0.00	0.63	0.85
2000	0.75	0.96	0.58	0.01	0.57	0.93
2001	0.82	0.82	0.51	0.00	0.51	0.79
2002	1.11	1.11	0.59	0.01	0.66	0.88
2003	1.04	1.11	0.62	0.01	0.66	0.92
2004	1.18	1.25	0.62	0.01	0.70	0.90
2005	1.04	1.25	0.69	0.03	0.71	0.99
2006	1.18	1.25	0.67	0.03	0.70	0.91
2007	1.18	1.32	0.64	0.02	0.72	0.93
2008	1.11	1.25	0.66	0.02	0.73	0.98
2009	1.11	1.32	0.69	0.04	0.76	1.01
2010	1.32	1.54	0.72	0.09	0.87	1.05
2011	1.39	1.39	0.72	0.07	0.83	0.97
2012	1.32	1.46	0.72	0.08	0.83	1.00
2013	1.11	1.25	0.70	0.08	0.79	1.06
2014	1.39	1.39	0.69	0.04	0.85	0.99
2015	1.25	1.32	0.69	0.03	0.75	0.94
2016	1.25	1.39	0.67	0.03	0.78	0.98
2017	1.39	1.46	0.70	0.08	0.85	0.99
2018	1.04	1.39	0.68	0.03	0.79	1.10
2019	1.18	1.39	0.67	0.03	0.78	1.00

Norway Loster FU2627 Females

Los datos del ciclo vital recogidos de la literatura son:

\(L_{mat}^{LIT}\) = 26 mm. Females FU2627 (Fariña, 1996).

\(L_{inf}^{LIT}\) = 65 cm. Females FU2627 (Fernánez et al., 1986).

\({M/k}^{LIT}\) =0.2/0.08=2.5 (k 0.08 year-1 y M=0.2 (Fernánez et al., 1986; Morizur, 1984).

wal <- read.csv("FU2627_PesosFemales_1988_2019_medio.csv", stringsAsFactors = FALSE)
freq <- read.csv("FU2627_tallasFemales_1988_2019.csv", stringsAsFactors = FALSE)
head(freq)

##   talla X1988  X1989  X1990 X1991 X1992 X1993 X1994 X1995 X1996 X1997 X1998
## 1    12     0      0      0     0     0     0     0     0     0     0     0
## 2    13     0   4239  15172     0     0     0     0     0     0     0     0
## 3    14     0   2474  25480     0     0     0     0     0     0     0     0
## 4    15     0 108363  61013  1795     0     0     0     0     0     0     0
## 5    16     0 113495 254545  9073     0     0     0     0     0     0     0
## 6    17     0  34688 529385 11820     0     0  2730     0     0     0     0
##   X1999 X2000 X2001 X2002 X2003 X2004 X2005 X2006 X2007 X2008 X2009 X2010 X2011
## 1     0     0     0     0     0     0     0     0     0     0     0     0     0
## 2     0     0     0     0     0     0     0     0     0     0     0     0     0
## 3     0     0     0     0     0     0     0     0     0     0     0     0     0
## 4     0     0     0     0     0     0     0     0     0     0     0     0     0
## 5     0  3063 13552     0     0     0     0     0     0     0     0     0     0
## 6     0  3063 11684     0     0     0     0     0     0     0     0     0     0
##   X2012 X2013 X2014 X2015 X2016 X2017 X2018 X2019
## 1     0     0     0     0     0     0     0     0
## 2     0     0     0     0     0     0     0     0
## 3     0     0     0     0     0     0     0     0
## 4     0     0     0     0     0     0     0     0
## 5     0     0     0     0     0     0     0     0
## 6     0     0     0     0     0     0     0     0

head(wal)

##   talla    X1988    X1989    X1990    X1991    X1992    X1993    X1994    X1995
## 1    12 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068
## 2    13 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439
## 3    14 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904
## 4    15 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656
## 5    16 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947
## 6    17 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080
##      X1996    X1997    X1998    X1999    X2000    X2001    X2002    X2003
## 1 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068
## 2 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439
## 3 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904
## 4 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656
## 5 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947
## 6 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080
##      X2004    X2005    X2006    X2007    X2008    X2009    X2010    X2011
## 1 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068
## 2 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439
## 3 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904
## 4 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656
## 5 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947
## 6 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080
##      X2012    X2013    X2014    X2015    X2016    X2017    X2018    X2019
## 1 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068 1.258068
## 2 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439 1.604439
## 3 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904 2.010904
## 4 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656 2.482656
## 5 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947 3.024947
## 6 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080 3.643080

bin_plot(freq, 1, "cm")

lb_tableSH(freq, 2, "mm", linf=65, lmat=26, mk_ratio=2.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.12	0.67	0.11	0.92	0.98
1989	0.81	0.88	0.66	0.06	0.80	1.01
1990	0.73	0.81	0.58	0.02	0.69	0.92
1991	0.88	0.96	0.68	0.07	0.84	0.99
1992	0.96	1.12	0.70	0.14	0.92	1.03
1993	0.96	1.04	0.70	0.14	0.92	1.03
1994	1.04	1.12	0.72	0.19	0.97	1.03
1995	1.04	1.04	0.67	0.09	0.91	0.96
1996	0.88	0.96	0.69	0.11	0.86	1.02
1997	1.12	1.19	0.75	0.24	1.00	1.01
1998	1.19	1.27	0.78	0.37	1.07	1.03
1999	1.19	1.27	0.78	0.40	1.08	1.04
2000	0.81	0.96	0.71	0.18	0.89	1.12
2001	0.81	0.88	0.69	0.08	0.79	0.99
2002	1.04	1.12	0.79	0.34	1.02	1.08
2003	1.12	1.12	0.74	0.25	1.01	1.02
2004	1.19	1.27	0.79	0.52	1.11	1.07
2005	1.12	1.27	0.83	0.45	1.09	1.10
2006	1.27	1.27	0.81	0.44	1.11	1.02
2007	1.27	1.27	0.81	0.39	1.09	1.01
2008	1.19	1.27	0.76	0.40	1.06	1.03
2009	1.12	1.27	0.85	0.46	1.08	1.10
2010	1.42	1.42	0.88	0.75	1.24	1.06
2011	1.35	1.42	0.89	0.73	1.23	1.09
2012	1.42	1.42	0.87	0.70	1.23	1.04
2013	1.50	1.42	0.93	0.71	1.31	1.07
2014	1.27	1.27	0.88	0.57	1.19	1.10
2015	1.27	1.35	0.84	0.53	1.12	1.04
2016	1.12	1.27	0.83	0.46	1.09	1.10
2017	1.35	1.42	0.99	0.73	1.27	1.13
2018	1.12	1.27	0.83	0.50	1.09	1.11
2019	1.12	1.35	0.85	0.67	1.16	1.18

# Primero infraestimando (${M/k}^{LIT}$ multiplicado por 0.75):

lb_tableSH(freq, 2, "mm", linf=65, lmat=26, mk_ratio=0.75*2.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.12	0.67	0.01	0.82	0.93
1989	0.81	0.88	0.66	0.02	0.71	0.94
1990	0.73	0.81	0.58	0.00	0.61	0.85
1991	0.88	0.96	0.68	0.02	0.74	0.93
1992	0.96	1.12	0.70	0.04	0.81	0.97
1993	0.96	1.04	0.70	0.03	0.81	0.97
1994	1.04	1.12	0.72	0.04	0.86	0.98
1995	1.04	1.04	0.67	0.02	0.80	0.92
1996	0.88	0.96	0.69	0.03	0.76	0.96
1997	1.12	1.19	0.75	0.08	0.88	0.97
1998	1.19	1.27	0.78	0.13	0.95	0.99
1999	1.19	1.27	0.78	0.14	0.96	1.00
2000	0.81	0.96	0.71	0.04	0.79	1.05
2001	0.81	0.88	0.69	0.02	0.70	0.92
2002	1.04	1.12	0.79	0.11	0.90	1.03
2003	1.12	1.12	0.74	0.07	0.89	0.98
2004	1.19	1.27	0.79	0.17	0.98	1.03
2005	1.12	1.27	0.83	0.22	0.96	1.05
2006	1.27	1.27	0.81	0.12	0.98	0.99
2007	1.27	1.27	0.81	0.12	0.97	0.97
2008	1.19	1.27	0.76	0.10	0.94	0.99
2009	1.12	1.27	0.85	0.17	0.96	1.05
2010	1.42	1.42	0.88	0.39	1.10	1.03
2011	1.35	1.42	0.89	0.41	1.09	1.06
2012	1.42	1.42	0.87	0.28	1.09	1.01
2013	1.50	1.42	0.93	0.38	1.16	1.04
2014	1.27	1.27	0.88	0.31	1.05	1.06
2015	1.27	1.35	0.84	0.15	1.00	1.00
2016	1.12	1.27	0.83	0.27	0.96	1.05
2017	1.35	1.42	0.99	0.51	1.13	1.09
2018	1.12	1.27	0.83	0.26	0.97	1.06
2019	1.12	1.35	0.85	0.37	1.03	1.13

# Segundo sobrestimando (${M/k}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 2, "mm", linf=65, lmat=26, mk_ratio=1.25*2.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.12	0.67	0.18	1.02	1.01
1989	0.81	0.88	0.66	0.10	0.90	1.05
1990	0.73	0.81	0.58	0.03	0.77	0.97
1991	0.88	0.96	0.68	0.11	0.93	1.03
1992	0.96	1.12	0.70	0.20	1.02	1.07
1993	0.96	1.04	0.70	0.22	1.02	1.06
1994	1.04	1.12	0.72	0.30	1.08	1.06
1995	1.04	1.04	0.67	0.14	1.01	1.00
1996	0.88	0.96	0.69	0.17	0.96	1.06
1997	1.12	1.19	0.75	0.33	1.11	1.04
1998	1.19	1.27	0.78	0.49	1.19	1.06
1999	1.19	1.27	0.78	0.54	1.20	1.07
2000	0.81	0.96	0.71	0.25	1.00	1.17
2001	0.81	0.88	0.69	0.12	0.88	1.03
2002	1.04	1.12	0.79	0.43	1.13	1.12
2003	1.12	1.12	0.74	0.37	1.12	1.05
2004	1.19	1.27	0.79	0.65	1.24	1.10
2005	1.12	1.27	0.83	0.56	1.21	1.13
2006	1.27	1.27	0.81	0.60	1.23	1.05
2007	1.27	1.27	0.81	0.54	1.21	1.03
2008	1.19	1.27	0.76	0.52	1.18	1.06
2009	1.12	1.27	0.85	0.58	1.21	1.13
2010	1.42	1.42	0.88	0.84	1.38	1.08
2011	1.35	1.42	0.89	0.81	1.37	1.12
2012	1.42	1.42	0.87	0.81	1.36	1.06
2013	1.50	1.42	0.93	0.76	1.46	1.09
2014	1.27	1.27	0.88	0.63	1.33	1.13
2015	1.27	1.35	0.84	0.69	1.25	1.06
2016	1.12	1.27	0.83	0.56	1.21	1.13
2017	1.35	1.42	0.99	0.85	1.42	1.15
2018	1.12	1.27	0.83	0.57	1.22	1.14
2019	1.12	1.35	0.85	0.75	1.30	1.22

# Tercero usando el valor por defecto de 1.5.

lb_tableSH(freq, 2, "mm", linf=65, lmat=26, mk_ratio=1.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.12	0.67	0.01	0.75	0.89
1989	0.81	0.88	0.66	0.00	0.66	0.89
1990	0.73	0.81	0.58	0.00	0.57	0.80
1991	0.88	0.96	0.68	0.01	0.68	0.89
1992	0.96	1.12	0.70	0.01	0.75	0.93
1993	0.96	1.04	0.70	0.01	0.75	0.93
1994	1.04	1.12	0.72	0.01	0.79	0.94
1995	1.04	1.04	0.67	0.00	0.74	0.88
1996	0.88	0.96	0.69	0.01	0.70	0.91
1997	1.12	1.19	0.75	0.02	0.82	0.93
1998	1.19	1.27	0.78	0.05	0.87	0.96
1999	1.19	1.27	0.78	0.04	0.88	0.97
2000	0.81	0.96	0.71	0.01	0.73	0.99
2001	0.81	0.88	0.69	0.01	0.64	0.87
2002	1.04	1.12	0.79	0.04	0.83	0.99
2003	1.12	1.12	0.74	0.02	0.83	0.94
2004	1.19	1.27	0.79	0.05	0.91	1.00
2005	1.12	1.27	0.83	0.09	0.89	1.01
2006	1.27	1.27	0.81	0.06	0.90	0.96
2007	1.27	1.27	0.81	0.05	0.89	0.94
2008	1.19	1.27	0.76	0.03	0.87	0.95
2009	1.12	1.27	0.85	0.08	0.89	1.01
2010	1.42	1.42	0.88	0.17	1.02	1.00
2011	1.35	1.42	0.89	0.23	1.01	1.03
2012	1.42	1.42	0.87	0.17	1.00	0.99
2013	1.50	1.42	0.93	0.28	1.07	1.02
2014	1.27	1.27	0.88	0.19	0.97	1.03
2015	1.27	1.35	0.84	0.08	0.92	0.97
2016	1.12	1.27	0.83	0.12	0.89	1.01
2017	1.35	1.42	0.99	0.26	1.04	1.06
2018	1.12	1.27	0.83	0.12	0.89	1.02
2019	1.12	1.35	0.85	0.15	0.95	1.09

# Primero infraestimando ($L_{inf}^{LIT}$ multiplicado por 0.75):

lb_tableSH(freq, 2, "mm", linf=0.75*65, lmat=26, mk_ratio=2.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.12	0.89	0.61	1.23	1.06
1989	0.81	0.88	0.88	0.32	1.07	1.11
1990	0.73	0.81	0.77	0.11	0.92	1.02
1991	0.88	0.96	0.90	0.36	1.12	1.09
1992	0.96	1.12	0.94	0.64	1.22	1.12
1993	0.96	1.04	0.93	0.60	1.22	1.12
1994	1.04	1.12	0.96	0.73	1.29	1.12
1995	1.04	1.04	0.89	0.58	1.21	1.05
1996	0.88	0.96	0.92	0.45	1.15	1.12
1997	1.12	1.19	1.00	0.79	1.33	1.10
1998	1.19	1.27	1.05	0.89	1.42	1.11
1999	1.19	1.27	1.04	0.91	1.44	1.13
2000	0.81	0.96	0.95	0.56	1.19	1.24
2001	0.81	0.88	0.92	0.27	1.05	1.09
2002	1.04	1.12	1.06	0.73	1.36	1.18
2003	1.12	1.12	0.99	0.73	1.35	1.11
2004	1.19	1.27	1.06	0.91	1.48	1.16
2005	1.12	1.27	1.10	0.86	1.45	1.19
2006	1.27	1.27	1.08	0.93	1.47	1.10
2007	1.27	1.27	1.08	0.94	1.45	1.08
2008	1.19	1.27	1.01	0.91	1.42	1.11
2009	1.12	1.27	1.13	0.85	1.44	1.19
2010	1.42	1.42	1.18	0.99	1.66	1.13
2011	1.35	1.42	1.19	0.98	1.64	1.17
2012	1.42	1.42	1.16	0.96	1.63	1.12
2013	1.50	1.42	1.24	0.95	1.75	1.14
2014	1.27	1.27	1.18	0.87	1.59	1.18
2015	1.27	1.35	1.12	0.97	1.50	1.12
2016	1.12	1.27	1.10	0.82	1.45	1.19
2017	1.35	1.42	1.32	1.00	1.70	1.21
2018	1.12	1.27	1.11	0.86	1.46	1.20
2019	1.12	1.35	1.13	0.93	1.55	1.28

# Segundo sobrestimando ($L_{inf}^{LIT}$ multiplicado por 1.25):

lb_tableSH(freq, 2, "mm", linf=1.25*65, lmat=26, mk_ratio=2.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	1.04	1.12	0.54	0.01	0.74	0.90
1989	0.81	0.88	0.53	0.00	0.64	0.92
1990	0.73	0.81	0.46	0.00	0.55	0.83
1991	0.88	0.96	0.54	0.01	0.67	0.91
1992	0.96	1.12	0.56	0.01	0.73	0.95
1993	0.96	1.04	0.56	0.01	0.73	0.94
1994	1.04	1.12	0.57	0.01	0.77	0.95
1995	1.04	1.04	0.54	0.00	0.73	0.89
1996	0.88	0.96	0.55	0.01	0.69	0.93
1997	1.12	1.19	0.60	0.02	0.80	0.94
1998	1.19	1.27	0.63	0.05	0.85	0.96
1999	1.19	1.27	0.62	0.04	0.86	0.97
2000	0.81	0.96	0.57	0.01	0.71	1.02
2001	0.81	0.88	0.55	0.01	0.63	0.90
2002	1.04	1.12	0.63	0.04	0.81	1.00
2003	1.12	1.12	0.59	0.02	0.81	0.95
2004	1.19	1.27	0.63	0.05	0.89	1.00
2005	1.12	1.27	0.66	0.09	0.87	1.02
2006	1.27	1.27	0.65	0.06	0.88	0.95
2007	1.27	1.27	0.65	0.05	0.87	0.94
2008	1.19	1.27	0.61	0.03	0.85	0.96
2009	1.12	1.27	0.68	0.08	0.87	1.02
2010	1.42	1.42	0.71	0.17	0.99	0.99
2011	1.35	1.42	0.71	0.23	0.99	1.02
2012	1.42	1.42	0.70	0.17	0.98	0.98
2013	1.50	1.42	0.74	0.28	1.05	1.01
2014	1.27	1.27	0.71	0.19	0.95	1.03
2015	1.27	1.35	0.67	0.08	0.90	0.97
2016	1.12	1.27	0.66	0.12	0.87	1.02
2017	1.35	1.42	0.79	0.26	1.02	1.06
2018	1.12	1.27	0.67	0.12	0.87	1.03
2019	1.12	1.35	0.68	0.15	0.93	1.09

Small Spotted Catshark

wal <- read.csv("Pin8c9awal.csv",sep=",")
head(wal)

##   MeanLength X2014 X2015 X2016 X2017 X2018 X2019
## 1       20.5  23.2  23.2  23.2  23.2  23.2  23.2
## 2       21.5  26.9  26.9  26.9  26.9  26.9  26.9
## 3       22.5  31.0  31.0  31.0  31.0  31.0  31.0
## 4       23.5  35.5  35.5  35.5  35.5  35.5  35.5
## 5       24.5  40.4  40.4  40.4  40.4  40.4  40.4
## 6       25.5  45.7  45.7  45.7  45.7  45.7  45.7

freq <- read.csv("Pin8c9afreq.csv", stringsAsFactors = FALSE)
head(freq)

##   MeanLength X2014 X2015 X2016 X2017 X2018 X2019
## 1       20.5     0     0     0     0     0     0
## 2       21.5     0     0     0     0     0     0
## 3       22.5     0     0     0     0     0     0
## 4       23.5     0     0     0     0     0     0
## 5       24.5     0     0     0     0     0     0
## 6       25.5     0     0     0     0     0     0

bin_plot(freq, 1, "cm")

## A blank LB_pars object created

bin_plot(freq, 2, "cm")

## A blank LB_pars object created

bin_plot(freq, 3, "cm")

## A blank LB_pars object created

## El escenario de REFERENCIA:
lb_tableSH(freq, 2, "cm", linf=75.0, lmat=54.2, mk_ratio=1.5,wal)

## Warning: FlexTable is deprecated, please use flextable::flextable() or
## flextable::regulartable() instead.

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2014	0.90	0.94	0.82	0.37	1.07	0.96
2015	0.90	0.90	0.83	0.36	1.08	0.97
2016	0.94	0.94	0.87	0.45	1.10	0.97
2017	0.90	0.90	0.83	0.29	1.07	0.96
2018	0.90	0.90	0.83	0.30	1.07	0.96
2019	0.90	0.90	0.82	0.30	1.06	0.96

## Probamos los escenarios 1) M/k infraestimando (M/k multiplicado por 0.75):
lb_tableSH(freq, 2, "cm", linf=75.0, lmat=54.2, mk_ratio=0.75*1.5,wal)

## Warning: FlexTable is deprecated, please use flextable::flextable() or
## flextable::regulartable() instead.

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2014	0.90	0.94	0.82	0.03	0.98	0.94
2015	0.90	0.90	0.83	0.05	0.99	0.94
2016	0.94	0.94	0.87	0.09	1.01	0.94
2017	0.90	0.90	0.83	0.04	0.98	0.94
2018	0.90	0.90	0.83	0.04	0.98	0.94
2019	0.90	0.90	0.82	0.04	0.98	0.93

## Probamos los escenarios 2) M/k sobreestimando (M/k multiplicado por 1.25):
lb_tableSH(freq, 2, "cm", linf=75.0, lmat=54.2, mk_ratio=1.25*1.5,wal)

## Warning: FlexTable is deprecated, please use flextable::flextable() or
## flextable::regulartable() instead.

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2014	0.90	0.94	0.82	0.78	1.16	0.98
2015	0.90	0.90	0.83	0.72	1.17	0.99
2016	0.94	0.94	0.87	0.84	1.19	0.98
2017	0.90	0.90	0.83	0.66	1.15	0.98
2018	0.90	0.90	0.83	0.67	1.16	0.98
2019	0.90	0.90	0.82	0.70	1.15	0.98

## Primero infraestimando (Linf Multiplicado por 0.75):
lb_tableSH(freq, 2, "cm", linf=0.75*75.0, lmat=54.2, mk_ratio=1.5,wal)

## Warning: FlexTable is deprecated, please use flextable::flextable() or
## flextable::regulartable() instead.

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2014	0.90	0.94	1.09	0.97	1.43	1.05
2015	0.90	0.90	1.11	0.93	1.44	1.06
2016	0.94	0.94	1.16	0.99	1.47	1.05
2017	0.90	0.90	1.10	0.96	1.42	1.05
2018	0.90	0.90	1.10	0.96	1.42	1.05
2019	0.90	0.90	1.09	0.99	1.42	1.05

## Segundo sobrestimando (Linf Multiplicado por 1.25):
lb_tableSH(freq, 2, "cm", linf=1.25*75.0, lmat=54.2, mk_ratio=1.5,wal)

## Warning: FlexTable is deprecated, please use flextable::flextable() or
## flextable::regulartable() instead.

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2014	0.90	0.94	0.65	0.00	0.86	0.89
2015	0.90	0.90	0.66	0.00	0.86	0.89
2016	0.94	0.94	0.70	0.01	0.88	0.89
2017	0.90	0.90	0.66	0.00	0.85	0.89
2018	0.90	0.90	0.66	0.00	0.85	0.89
2019	0.90	0.90	0.65	0.00	0.85	0.88

Anchovy

Los datos del ciclo vital recogidos de la literatura son:

\(L_{mat}^{LIT}\) = 11.2 cm (Millán 1999)

\({M/k}^{LIT}=1.3/0.9\)=1.44

\(L_{inf}^{LIT}\)=18.95 (k y \(L_{inf}\) de Bellido et al. 2000)

M = 1.3 (Razonamiento en WKPELA 2018 report, uso M para la edad 1 \(M_1\))

–>

MK<-1.44
Linf<-18.95
Lmat<-11.2
wal <- read.csv("wal_anchovy_fv.csv", stringsAsFactors = FALSE)
freq <- read.csv("lengthfreq_anchovy_fv.csv", stringsAsFactors = FALSE)
head(freq)

##   length X1988 X1989    X1990    X1991  X1992   X1993 X1994 X1995     X1996
## 1    3.5     0     0        0        0      0       0     0     0   1349286
## 2    4.0     0     0  4281037   171956   1527   48637     0     0  12676995
## 3    4.5     0     0 18371017  3937228  29018  706893     0     0  67819283
## 4    5.0 64688     0 32251146 54991246  90023 1831793     0     0 160893713
## 5    5.5 86251     0 46583672 80536890 368660 3246934     0     0 129791150
## 6    6.0     0     0 45810220 43303347 983188 5030957     0     0  52811605
##      X1997    X1998    X1999    X2000      X2001    X2002   X2003  X2004  X2005
## 1        0        0        0        0   282386.1    76904       0      0      0
## 2        0        0  1830574   113762   211277.3   274755   35584      0  16257
## 3  1333027  4655928 17055364   806404  1747585.3  1463072  116275  25370 130064
## 4 11492104 25824726 41100084  4886709  5808681.0  3870681  218084  53803 146322
## 5 38721933 57085884 36181025  9251152  9844138.0  8742129  653305 213296  81290
## 6 53185343 82441650 19366091 12753186 12499866.5 13778906 1763017 395900 445378
##    X2006 X2007 X2008 X2009 X2010 X2011  X2012 X2013 X2014 X2015 X2016  X2017
## 1      0     0     0     0     0     0      0     0     0     0     0      0
## 2      0     0     0     0     0     0      0     0     0     0     0      0
## 3      0     0     0     0     0     0      0     0     0     0     0      0
## 4      0     0     0     0     0     0      0     0     0     0     0  45462
## 5      0     0     0     0     0     0      0     0     0     0  9084  34097
## 6 372540     0     0     0     0     0 394206     0     0 80458 54503 217184
##    X2018 X2019
## 1      0     0
## 2      0     0
## 3      0  5047
## 4   5252  5047
## 5 122414     0
## 6 170751 19929

head(wal)

##   length     X1988     X1989     X1990     X1991     X1992     X1993     X1994
## 1    3.5 0.2518403 0.2092267 0.2271301 0.2180922 0.3299293 0.3550483 0.2759662
## 2    4.0 0.3770388 0.3210175 0.3446703 0.3339648 0.4823867 0.5143807 0.4116180
## 3    4.5 0.5396730 0.4696109 0.4993023 0.4877011 0.6760814 0.7150791 0.5872153
## 4    5.0 0.7452009 0.6612985 0.6969456 0.6856975 0.9160444 0.9618145 0.8084307
## 5    5.5 0.9992115 0.9026572 0.9437311 0.9346291 1.2073248 1.2592391 1.0810548
## 6    6.0 1.3074143 1.2005329 1.2459871 1.2414337 1.5549890 1.6119883 1.4109861
##       X1995     X1996     X1997     X1998     X1999     X2000     X2001
## 1 0.2759662 0.2660571 0.2890663 0.2109831 0.2001816 0.2449791 0.2620221
## 2 0.4116180 0.3960943 0.4288719 0.3227909 0.3081657 0.3695502 0.3950267
## 3 0.5872153 0.5641280 0.6089467 0.4710105 0.4521485 0.5325203 0.5689337
## 4 0.8084307 0.7754821 0.8347932 0.6617593 0.6384087 0.7397834 0.7899969
## 5 1.0810548 1.0355821 1.1120032 0.9014165 0.8735282 0.9974136 1.0646578
## 6 1.4109861 1.3499475 1.4462498 1.1966083 1.1643759 1.3116520 1.3995322
##       X2002     X2003     X2004     X2005     X2006     X2007     X2008
## 1 0.2161115 0.2690808 0.2644649 0.2566905 0.2460155 0.2929484 0.3418905
## 2 0.3314068 0.4029565 0.3953278 0.3863321 0.3687180 0.4345656 0.5011364
## 3 0.4845831 0.5769057 0.5650740 0.5555725 0.5282721 0.6169477 0.7039346
## 4 0.6820956 0.7967816 0.7793116 0.7703975 0.7300911 0.8456590 0.9557075
## 5 0.9306895 1.0685792 1.0437756 1.0369636 0.9797234 1.1263528 1.2619092
## 6 1.2373830 1.3984243 1.3643180 1.3615860 1.2828419 1.4647644 1.6280227
##       X2009     X2010     X2011     X2012     X2013     X2014     X2015
## 1 0.2619156 0.3055713 0.2545966 0.2606879 0.2619059 0.2192163 0.2412433
## 2 0.3944381 0.4508095 0.3813615 0.3935505 0.3925561 0.3362669 0.3636509
## 3 0.5675389 0.6368953 0.5461100 0.5674935 0.5624538 0.4918181 0.5236817
## 4 0.7873773 0.8691786 0.7543998 0.7888552 0.7773667 0.6924424 0.7270830
## 5 1.0602915 1.1530702 1.0119242 1.0641714 1.0432063 0.9450092 0.9797736
## 6 1.3927860 1.4940365 1.3245022 1.4001616 1.3660173 1.2566676 1.2878320
##       X2016     X2017     X2018     X2019
## 1 0.2428885 0.3741121 0.3225905 0.3050406
## 2 0.3695925 0.5416183 0.4751011 0.4500820
## 3 0.5367072 0.7524734 0.6701900 0.6359370
## 4 0.7507957 1.0115421 0.9133608 0.8679562
## 5 1.0186707 1.3236670 1.2101712 1.1515516
## 6 1.3473791 1.6936699 1.5662289 1.4921912

bin_plot(freq, 1, "cm")

bin_plot(freq, 2, "cm")

bin_plot(freq, 3, "cm")

bin_plot(freq, 4, "cm")

lb_tableSH(freq, 4, "cm", linf=Linf, lmat=Lmat, mk_ratio=MK ,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	0.89	0.89	0.77	0.01	0.85	0.89
1989	0.89	0.89	0.84	0.02	0.85	0.88
1990	0.89	0.54	0.74	0.00	0.82	0.85
1991	0.54	0.54	0.76	0.01	0.73	1.01
1992	0.89	0.89	0.74	0.00	0.85	0.88
1993	0.89	0.89	0.74	0.00	0.94	0.98
1994	0.89	0.89	0.75	0.00	0.87	0.90
1995	0.89	0.89	0.74	0.00	0.83	0.86
1996	0.54	0.54	0.72	0.00	0.55	0.75
1997	0.54	0.54	0.74	0.00	0.72	0.99
1998	0.89	0.54	0.74	0.00	0.83	0.86
1999	0.54	0.54	0.74	0.00	0.79	1.08
2000	0.89	0.54	0.74	0.00	0.85	0.88
2001	0.89	0.89	0.80	0.02	0.93	0.97
2002	0.89	0.89	0.75	0.00	0.89	0.93
2003	0.89	0.89	0.75	0.00	0.88	0.91
2004	0.89	0.89	0.74	0.00	0.87	0.90
2005	0.89	0.89	0.74	0.00	0.82	0.86
2006	0.89	0.89	0.74	0.00	0.84	0.88
2007	0.89	0.89	0.74	0.00	0.84	0.87
2008	0.89	0.89	0.76	0.01	0.96	1.00
2009	0.89	0.89	0.74	0.00	0.93	0.97
2010	0.89	0.89	0.74	0.00	0.87	0.91
2011	0.89	0.89	0.74	0.00	0.85	0.88
2012	0.89	0.89	0.75	0.00	0.93	0.97
2013	0.89	0.89	0.74	0.00	0.88	0.91
2014	0.89	0.89	0.74	0.00	0.85	0.88
2015	0.89	0.89	0.75	0.00	0.86	0.89
2016	0.89	0.89	0.75	0.00	0.90	0.93
2017	0.89	0.89	0.74	0.00	0.81	0.84
2018	0.89	0.89	0.74	0.00	0.90	0.94
2019	0.89	0.89	0.75	0.00	0.86	0.90

lb_tableSH(freq, 4, "cm", linf=Linf, lmat=Lmat, mk_ratio=MK*0.75,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	0.89	0.89	0.77	0.01	0.78	0.85
1989	0.89	0.89	0.84	0.02	0.78	0.85
1990	0.89	0.54	0.74	0.00	0.75	0.81
1991	0.54	0.54	0.76	0.01	0.68	0.93
1992	0.89	0.89	0.74	0.00	0.78	0.85
1993	0.89	0.89	0.74	0.00	0.86	0.94
1994	0.89	0.89	0.75	0.00	0.79	0.86
1995	0.89	0.89	0.74	0.00	0.76	0.83
1996	0.54	0.54	0.72	0.00	0.50	0.69
1997	0.54	0.54	0.74	0.00	0.66	0.91
1998	0.89	0.54	0.74	0.00	0.76	0.83
1999	0.54	0.54	0.74	0.00	0.72	1.00
2000	0.89	0.54	0.74	0.00	0.78	0.85
2001	0.89	0.89	0.80	0.02	0.86	0.93
2002	0.89	0.89	0.75	0.00	0.82	0.89
2003	0.89	0.89	0.75	0.00	0.81	0.88
2004	0.89	0.89	0.74	0.00	0.80	0.86
2005	0.89	0.89	0.74	0.00	0.76	0.82
2006	0.89	0.89	0.74	0.00	0.77	0.84
2007	0.89	0.89	0.74	0.00	0.77	0.83
2008	0.89	0.89	0.76	0.01	0.88	0.96
2009	0.89	0.89	0.74	0.00	0.85	0.93
2010	0.89	0.89	0.74	0.00	0.80	0.87
2011	0.89	0.89	0.74	0.00	0.78	0.85
2012	0.89	0.89	0.75	0.00	0.86	0.93
2013	0.89	0.89	0.74	0.00	0.81	0.87
2014	0.89	0.89	0.74	0.00	0.78	0.85
2015	0.89	0.89	0.75	0.00	0.79	0.85
2016	0.89	0.89	0.75	0.00	0.82	0.89
2017	0.89	0.89	0.74	0.00	0.74	0.81
2018	0.89	0.89	0.74	0.00	0.83	0.90
2019	0.89	0.89	0.75	0.00	0.79	0.86

lb_tableSH(freq, 4, "cm", linf=Linf, lmat=Lmat, mk_ratio=MK*1.25,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	0.89	0.89	0.77	0.22	0.92	0.91
1989	0.89	0.89	0.84	0.19	0.92	0.91
1990	0.89	0.54	0.74	0.08	0.88	0.87
1991	0.54	0.54	0.76	0.19	0.79	1.07
1992	0.89	0.89	0.74	0.19	0.92	0.91
1993	0.89	0.89	0.74	0.41	1.01	1.01
1994	0.89	0.89	0.75	0.22	0.94	0.93
1995	0.89	0.89	0.74	0.15	0.90	0.89
1996	0.54	0.54	0.72	0.05	0.59	0.79
1997	0.54	0.54	0.74	0.26	0.78	1.04
1998	0.89	0.54	0.74	0.11	0.90	0.89
1999	0.54	0.54	0.74	0.32	0.85	1.14
2000	0.89	0.54	0.74	0.15	0.92	0.91
2001	0.89	0.89	0.80	0.41	1.01	1.00
2002	0.89	0.89	0.75	0.32	0.97	0.96
2003	0.89	0.89	0.75	0.29	0.95	0.94
2004	0.89	0.89	0.74	0.27	0.94	0.93
2005	0.89	0.89	0.74	0.13	0.89	0.88
2006	0.89	0.89	0.74	0.19	0.91	0.90
2007	0.89	0.89	0.74	0.17	0.90	0.90
2008	0.89	0.89	0.76	0.57	1.04	1.03
2009	0.89	0.89	0.74	0.47	1.00	1.00
2010	0.89	0.89	0.74	0.29	0.94	0.93
2011	0.89	0.89	0.74	0.21	0.92	0.91
2012	0.89	0.89	0.75	0.47	1.01	1.00
2013	0.89	0.89	0.74	0.30	0.95	0.94
2014	0.89	0.89	0.74	0.22	0.92	0.91
2015	0.89	0.89	0.75	0.24	0.93	0.92
2016	0.89	0.89	0.75	0.37	0.97	0.96
2017	0.89	0.89	0.74	0.09	0.88	0.87
2018	0.89	0.89	0.74	0.38	0.97	0.97
2019	0.89	0.89	0.75	0.25	0.93	0.92

lb_tableSH(freq, 4, "cm", linf=Linf, lmat=Lmat, mk_ratio=1.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	0.89	0.89	0.77	0.22	0.86	0.89
1989	0.89	0.89	0.84	0.19	0.86	0.89
1990	0.89	0.54	0.74	0.08	0.83	0.85
1991	0.54	0.54	0.76	0.19	0.74	1.02
1992	0.89	0.89	0.74	0.19	0.86	0.89
1993	0.89	0.89	0.74	0.41	0.95	0.98
1994	0.89	0.89	0.75	0.22	0.88	0.91
1995	0.89	0.89	0.74	0.15	0.84	0.87
1996	0.54	0.54	0.72	0.05	0.55	0.76
1997	0.54	0.54	0.74	0.26	0.73	1.00
1998	0.89	0.54	0.74	0.11	0.84	0.87
1999	0.54	0.54	0.74	0.32	0.80	1.09
2000	0.89	0.54	0.74	0.15	0.86	0.89
2001	0.89	0.89	0.80	0.41	0.94	0.98
2002	0.89	0.89	0.75	0.32	0.91	0.94
2003	0.89	0.89	0.75	0.29	0.89	0.92
2004	0.89	0.89	0.74	0.27	0.88	0.91
2005	0.89	0.89	0.74	0.13	0.84	0.86
2006	0.89	0.89	0.74	0.19	0.85	0.88
2007	0.89	0.89	0.74	0.17	0.85	0.88
2008	0.89	0.89	0.76	0.57	0.98	1.01
2009	0.89	0.89	0.74	0.47	0.94	0.97
2010	0.89	0.89	0.74	0.29	0.88	0.91
2011	0.89	0.89	0.74	0.21	0.86	0.89
2012	0.89	0.89	0.75	0.47	0.95	0.98
2013	0.89	0.89	0.74	0.30	0.89	0.92
2014	0.89	0.89	0.74	0.22	0.86	0.89
2015	0.89	0.89	0.75	0.24	0.87	0.90
2016	0.89	0.89	0.75	0.37	0.91	0.94
2017	0.89	0.89	0.74	0.09	0.82	0.85
2018	0.89	0.89	0.74	0.38	0.91	0.94
2019	0.89	0.89	0.75	0.25	0.87	0.90

lb_tableSH(freq, 4, "cm", linf=Linf*0.75, lmat=Lmat, mk_ratio=MK,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	0.89	0.89	1.02	0.22	1.14	0.98
1989	0.89	0.89	1.12	0.19	1.13	0.98
1990	0.89	0.54	0.99	0.08	1.09	0.94
1991	0.54	0.54	1.02	0.19	0.98	1.16
1992	0.89	0.89	0.99	0.19	1.13	0.98
1993	0.89	0.89	0.99	0.41	1.25	1.08
1994	0.89	0.89	1.00	0.22	1.15	1.00
1995	0.89	0.89	0.99	0.15	1.11	0.96
1996	0.54	0.54	0.96	0.05	0.73	0.86
1997	0.54	0.54	0.99	0.26	0.96	1.13
1998	0.89	0.54	0.99	0.11	1.11	0.96
1999	0.54	0.54	0.99	0.32	1.05	1.24
2000	0.89	0.54	0.99	0.15	1.13	0.98
2001	0.89	0.89	1.07	0.41	1.24	1.08
2002	0.89	0.89	1.00	0.32	1.19	1.03
2003	0.89	0.89	1.00	0.29	1.17	1.01
2004	0.89	0.89	0.99	0.27	1.15	1.00
2005	0.89	0.89	0.99	0.13	1.10	0.95
2006	0.89	0.89	0.99	0.19	1.12	0.97
2007	0.89	0.89	0.99	0.17	1.12	0.97
2008	0.89	0.89	1.01	0.57	1.28	1.11
2009	0.89	0.89	0.99	0.47	1.24	1.07
2010	0.89	0.89	0.99	0.29	1.16	1.01
2011	0.89	0.89	0.99	0.21	1.13	0.98
2012	0.89	0.89	1.00	0.47	1.25	1.08
2013	0.89	0.89	0.99	0.30	1.17	1.01
2014	0.89	0.89	0.99	0.22	1.13	0.98
2015	0.89	0.89	0.99	0.24	1.14	0.99
2016	0.89	0.89	0.99	0.37	1.19	1.03
2017	0.89	0.89	0.99	0.09	1.08	0.94
2018	0.89	0.89	0.99	0.38	1.20	1.04
2019	0.89	0.89	1.00	0.25	1.15	0.99

lb_tableSH(freq, 4, "cm", linf=Linf*1.25, lmat=Lmat, mk_ratio=MK,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1988	0.89	0.89	0.61	0.01	0.68	0.81
1989	0.89	0.89	0.67	0.02	0.68	0.80
1990	0.89	0.54	0.59	0.00	0.65	0.77
1991	0.54	0.54	0.61	0.01	0.59	0.89
1992	0.89	0.89	0.59	0.00	0.68	0.80
1993	0.89	0.89	0.59	0.00	0.75	0.89
1994	0.89	0.89	0.60	0.00	0.69	0.82
1995	0.89	0.89	0.59	0.00	0.66	0.78
1996	0.54	0.54	0.58	0.00	0.44	0.66
1997	0.54	0.54	0.59	0.00	0.58	0.87
1998	0.89	0.54	0.59	0.00	0.66	0.79
1999	0.54	0.54	0.59	0.00	0.63	0.95
2000	0.89	0.54	0.59	0.00	0.68	0.80
2001	0.89	0.89	0.64	0.02	0.75	0.88
2002	0.89	0.89	0.60	0.00	0.72	0.85
2003	0.89	0.89	0.60	0.00	0.70	0.83
2004	0.89	0.89	0.59	0.00	0.69	0.82
2005	0.89	0.89	0.59	0.00	0.66	0.78
2006	0.89	0.89	0.59	0.00	0.67	0.80
2007	0.89	0.89	0.59	0.00	0.67	0.79
2008	0.89	0.89	0.61	0.01	0.77	0.91
2009	0.89	0.89	0.59	0.00	0.74	0.88
2010	0.89	0.89	0.59	0.00	0.70	0.82
2011	0.89	0.89	0.59	0.00	0.68	0.80
2012	0.89	0.89	0.60	0.00	0.75	0.88
2013	0.89	0.89	0.59	0.00	0.70	0.83
2014	0.89	0.89	0.59	0.00	0.68	0.80
2015	0.89	0.89	0.60	0.00	0.68	0.81
2016	0.89	0.89	0.60	0.00	0.72	0.85
2017	0.89	0.89	0.59	0.00	0.65	0.77
2018	0.89	0.89	0.59	0.00	0.72	0.85
2019	0.89	0.89	0.60	0.00	0.69	0.82

Pollack

freq <- read.csv("Pol89afreq.csv", stringsAsFactors = FALSE)
head(freq)

##   MeanLength X2010 X2011 X2012 X2013 X2014 X2015 X2016  X2017 X2018
## 1       15.5     0     0     0     0     0 0.000     0  1.130     0
## 2       16.5     0     0     0     0     0 0.000     0  0.000     0
## 3       17.5     0     0     0     0     0 0.000     0  2.542     0
## 4       18.5     0     0     0     0     0 0.000     0  3.672     0
## 5       19.5     0     0     0     0     0 4.862     0  6.215     0
## 6       20.5     0     0     0     0     0 4.862     0 12.994     0

head(wal)

##   length     X1988     X1989     X1990     X1991     X1992     X1993     X1994
## 1    3.5 0.2518403 0.2092267 0.2271301 0.2180922 0.3299293 0.3550483 0.2759662
## 2    4.0 0.3770388 0.3210175 0.3446703 0.3339648 0.4823867 0.5143807 0.4116180
## 3    4.5 0.5396730 0.4696109 0.4993023 0.4877011 0.6760814 0.7150791 0.5872153
## 4    5.0 0.7452009 0.6612985 0.6969456 0.6856975 0.9160444 0.9618145 0.8084307
## 5    5.5 0.9992115 0.9026572 0.9437311 0.9346291 1.2073248 1.2592391 1.0810548
## 6    6.0 1.3074143 1.2005329 1.2459871 1.2414337 1.5549890 1.6119883 1.4109861
##       X1995     X1996     X1997     X1998     X1999     X2000     X2001
## 1 0.2759662 0.2660571 0.2890663 0.2109831 0.2001816 0.2449791 0.2620221
## 2 0.4116180 0.3960943 0.4288719 0.3227909 0.3081657 0.3695502 0.3950267
## 3 0.5872153 0.5641280 0.6089467 0.4710105 0.4521485 0.5325203 0.5689337
## 4 0.8084307 0.7754821 0.8347932 0.6617593 0.6384087 0.7397834 0.7899969
## 5 1.0810548 1.0355821 1.1120032 0.9014165 0.8735282 0.9974136 1.0646578
## 6 1.4109861 1.3499475 1.4462498 1.1966083 1.1643759 1.3116520 1.3995322
##       X2002     X2003     X2004     X2005     X2006     X2007     X2008
## 1 0.2161115 0.2690808 0.2644649 0.2566905 0.2460155 0.2929484 0.3418905
## 2 0.3314068 0.4029565 0.3953278 0.3863321 0.3687180 0.4345656 0.5011364
## 3 0.4845831 0.5769057 0.5650740 0.5555725 0.5282721 0.6169477 0.7039346
## 4 0.6820956 0.7967816 0.7793116 0.7703975 0.7300911 0.8456590 0.9557075
## 5 0.9306895 1.0685792 1.0437756 1.0369636 0.9797234 1.1263528 1.2619092
## 6 1.2373830 1.3984243 1.3643180 1.3615860 1.2828419 1.4647644 1.6280227
##       X2009     X2010     X2011     X2012     X2013     X2014     X2015
## 1 0.2619156 0.3055713 0.2545966 0.2606879 0.2619059 0.2192163 0.2412433
## 2 0.3944381 0.4508095 0.3813615 0.3935505 0.3925561 0.3362669 0.3636509
## 3 0.5675389 0.6368953 0.5461100 0.5674935 0.5624538 0.4918181 0.5236817
## 4 0.7873773 0.8691786 0.7543998 0.7888552 0.7773667 0.6924424 0.7270830
## 5 1.0602915 1.1530702 1.0119242 1.0641714 1.0432063 0.9450092 0.9797736
## 6 1.3927860 1.4940365 1.3245022 1.4001616 1.3660173 1.2566676 1.2878320
##       X2016     X2017     X2018     X2019
## 1 0.2428885 0.3741121 0.3225905 0.3050406
## 2 0.3695925 0.5416183 0.4751011 0.4500820
## 3 0.5367072 0.7524734 0.6701900 0.6359370
## 4 0.7507957 1.0115421 0.9133608 0.8679562
## 5 1.0186707 1.3236670 1.2101712 1.1515516
## 6 1.3473791 1.6936699 1.5662289 1.4921912

bin_plot(freq, 4, "cm")

wal <- read.csv("Pol89awal.csv", stringsAsFactors = FALSE)
lb_tableSH(freq, 4, "cm", linf=98.2, lmat=42.3, mk_ratio=1.648352,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2010	0.80	0.80	0.72	0.03	0.67	0.87
2011	1.18	1.18	0.80	0.07	0.91	0.94
2012	1.18	1.18	0.80	0.11	0.95	0.98
2013	1.09	1.09	0.79	0.12	0.89	0.97
2014	0.80	0.99	0.77	0.10	0.83	1.08
2015	0.71	0.80	0.74	0.04	0.70	0.96
2016	0.80	0.90	0.71	0.03	0.71	0.93
2017	0.80	0.90	0.80	0.09	0.79	1.02
2018	0.80	0.99	0.82	0.11	0.86	1.12

lb_tableSH(freq, 4, "cm", linf=98.2, lmat=42.3, mk_ratio=0.75*1.648352,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2010	0.80	0.80	0.72	0.01	0.61	0.81
2011	1.18	1.18	0.80	0.02	0.83	0.90
2012	1.18	1.18	0.80	0.03	0.86	0.94
2013	1.09	1.09	0.79	0.01	0.81	0.92
2014	0.80	0.99	0.77	0.01	0.76	1.01
2015	0.71	0.80	0.74	0.01	0.64	0.89
2016	0.80	0.90	0.71	0.01	0.65	0.86
2017	0.80	0.90	0.80	0.03	0.72	0.95
2018	0.80	0.99	0.82	0.05	0.79	1.04

lb_tableSH(freq, 4, "cm", linf=98.2, lmat=42.3, mk_ratio=1.25*1.648352,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2010	0.80	0.80	0.72	0.07	0.73	0.91
2011	1.18	1.18	0.80	0.11	0.99	0.97
2012	1.18	1.18	0.80	0.22	1.03	1.01
2013	1.09	1.09	0.79	0.18	0.97	1.00
2014	0.80	0.99	0.77	0.16	0.91	1.14
2015	0.71	0.80	0.74	0.07	0.76	1.02
2016	0.80	0.90	0.71	0.04	0.78	0.97
2017	0.80	0.90	0.80	0.14	0.86	1.08
2018	0.80	0.99	0.82	0.19	0.94	1.17

lb_tableSH(freq, 4, "cm", linf=98.2, lmat=42.3, mk_ratio=1.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2010	0.80	0.80	0.72	0.02	0.65	0.85
2011	1.18	1.18	0.80	0.04	0.88	0.93
2012	1.18	1.18	0.80	0.06	0.91	0.97
2013	1.09	1.09	0.79	0.08	0.86	0.95
2014	0.80	0.99	0.77	0.05	0.81	1.06
2015	0.71	0.80	0.74	0.02	0.68	0.94
2016	0.80	0.90	0.71	0.02	0.69	0.90
2017	0.80	0.90	0.80	0.06	0.76	1.00
2018	0.80	0.99	0.82	0.07	0.83	1.09

lb_tableSH(freq, 4, "cm", linf=0.75*98.2, lmat=42.3, mk_ratio=1.648352,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2010	0.80	0.80	0.96	0.14	0.89	0.98
2011	1.18	1.18	1.06	0.66	1.21	1.04
2012	1.18	1.18	1.07	0.69	1.26	1.08
2013	1.09	1.09	1.05	0.52	1.19	1.07
2014	0.80	0.99	1.02	0.58	1.11	1.22
2015	0.71	0.80	0.98	0.23	0.93	1.10
2016	0.80	0.90	0.94	0.18	0.95	1.05
2017	0.80	0.90	1.07	0.33	1.05	1.16
2018	0.80	0.99	1.09	0.61	1.15	1.26

lb_tableSH(freq, 4, "cm", linf=1.25*98.2, lmat=42.3, mk_ratio=1.648352,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
2010	0.80	0.80	0.58	0.00	0.54	0.78
2011	1.18	1.18	0.64	0.01	0.73	0.86
2012	1.18	1.18	0.64	0.00	0.76	0.89
2013	1.09	1.09	0.63	0.00	0.71	0.88
2014	0.80	0.99	0.61	0.00	0.67	0.97
2015	0.71	0.80	0.59	0.00	0.56	0.86
2016	0.80	0.90	0.57	0.00	0.57	0.83
2017	0.80	0.90	0.64	0.00	0.63	0.92
2018	0.80	0.99	0.65	0.00	0.69	1.00

Blackspot Seabream

Linf<-62 # Fixed to larger sample from the SoG
Lmat<-33 # Estimated from Gil (2006) Sex change TL in cm

wal <- read.csv("SBR9_mw.csv", stringsAsFactors = FALSE)
freq <- read.csv("SBR9_numbers.csv", stringsAsFactors = FALSE)
Linf<-62
Lmat<-33
MK<-1.42

head(freq)

##   MeanLength X1997 X1998 X1999 X2000 X2001 X2002 X2003 X2004 X2005 X2006 X2007
## 1       24.5   422   170     0     0     0     0     0     0     0     0     0
## 2       25.5  1553   718     0     0     0     0     0     0     0     0     0
## 3       26.5  9222  6454   527    48    42    91    52     0     0     0     0
## 4       27.5 33437 25121  2840   717   912   376   599     0  1012  1583   138
## 5       28.5 69291 53905  9521  3875  3214  2266  3516   254  7417 11301  1224
## 6       29.5 81193 66854 13037 11083 11024  8050 10162  2416 15187 27559  9655
##   X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015 X2016 X2017 X2018 X2019
## 1     0     0     0     0     0     0     0     0     0     0     0     0
## 2     0     0     0     0     0     0     0     0     0     0     0     0
## 3     0     0     0     0     0     0     0     0     0     0     0     0
## 4     0     0     0     0     0     0     0     0     0     0     0     0
## 5   160   267   285   742     0     0     0     0     0     0     0     0
## 6  6810  2139  7243 12657   872     0     0     0   160     0     0     0

head(wal)

##   MeanLength  X1997  X1998  X1999  X2000  X2001  X2002  X2003  X2004  X2005
## 1       24.5 197.92 197.92 197.92 197.92 197.92 197.92 197.92 197.92 197.92
## 2       25.5 224.41 224.41 224.41 224.41 224.41 224.41 224.41 224.41 224.41
## 3       26.5 253.22 253.22 253.22 253.22 253.22 253.22 253.22 253.22 253.22
## 4       27.5 284.45 284.45 284.45 284.45 284.45 284.45 284.45 284.45 284.45
## 5       28.5 318.21 318.21 318.21 318.21 318.21 318.21 318.21 318.21 318.21
## 6       29.5 354.60 354.60 354.60 354.60 354.60 354.60 354.60 354.60 354.60
##    X2006  X2007  X2008  X2009  X2010  X2011  X2012  X2013  X2014  X2015  X2016
## 1 197.92 197.92 197.92 197.92 197.92 197.92 197.92 197.92 197.92 197.92 197.92
## 2 224.41 224.41 224.41 224.41 224.41 224.41 224.41 224.41 224.41 224.41 224.41
## 3 253.22 253.22 253.22 253.22 253.22 253.22 253.22 253.22 253.22 253.22 253.22
## 4 284.45 284.45 284.45 284.45 284.45 284.45 284.45 284.45 284.45 284.45 284.45
## 5 318.21 318.21 318.21 318.21 318.21 318.21 318.21 318.21 318.21 318.21 318.21
## 6 354.60 354.60 354.60 354.60 354.60 354.60 354.60 354.60 354.60 354.60 354.60
##    X2017  X2018  X2019
## 1 197.92 197.92 197.92
## 2 224.41 224.41 224.41
## 3 253.22 253.22 253.22
## 4 284.45 284.45 284.45
## 5 318.21 318.21 318.21
## 6 354.60 354.60 354.60

bin_plot(freq, 1, "cm")

bin_plot(freq, 2, "cm")

bin_plot(freq, 3, "cm")

bin_plot(freq, 4, "cm")

lb_tableSH(freq, 2, "cm", linf=Linf, lmat=Lmat, mk_ratio=MK ,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1997	0.88	0.94	0.82	0.11	0.86	0.97
1998	0.88	0.94	0.78	0.04	0.82	0.92
1999	0.94	1.00	0.80	0.07	0.87	0.94
2000	1.00	1.00	0.80	0.06	0.90	0.93
2001	0.94	1.00	0.82	0.09	0.89	0.96
2002	0.94	1.00	0.83	0.11	0.92	0.99
2003	0.94	1.00	0.83	0.13	0.93	1.00
2004	0.94	1.00	0.82	0.08	0.87	0.94
2005	0.94	1.00	0.82	0.11	0.89	0.95
2006	0.94	0.94	0.81	0.07	0.87	0.93
2007	0.94	1.00	0.83	0.11	0.89	0.96
2008	0.94	1.00	0.84	0.14	0.90	0.97
2009	0.94	1.00	0.85	0.16	0.91	0.98
2010	0.94	1.00	0.82	0.08	0.86	0.93
2011	0.94	0.94	0.84	0.12	0.87	0.94
2012	0.94	1.00	0.84	0.11	0.87	0.93
2013	1.00	1.00	0.75	0.02	0.84	0.87
2014	1.00	1.00	0.83	0.08	0.89	0.93
2015	1.00	1.06	0.85	0.15	0.94	0.97
2016	0.94	1.00	0.82	0.09	0.89	0.96
2017	1.00	1.06	0.80	0.06	0.90	0.93
2018	1.00	1.06	0.81	0.07	0.90	0.93
2019	1.00	1.00	0.79	0.05	0.89	0.92

#1a. Underestimate M/k (*0.75):

lb_tableSH(freq, 2, "cm", linf=Linf, lmat=Lmat, mk_ratio=MK*0.75,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1997	0.88	0.94	0.82	0.03	0.79	0.92
1998	0.88	0.94	0.78	0.01	0.76	0.88
1999	0.94	1.00	0.80	0.02	0.80	0.90
2000	1.00	1.00	0.80	0.02	0.82	0.89
2001	0.94	1.00	0.82	0.03	0.82	0.92
2002	0.94	1.00	0.83	0.04	0.85	0.95
2003	0.94	1.00	0.83	0.04	0.85	0.95
2004	0.94	1.00	0.82	0.03	0.80	0.90
2005	0.94	1.00	0.82	0.03	0.82	0.91
2006	0.94	0.94	0.81	0.02	0.80	0.89
2007	0.94	1.00	0.83	0.04	0.82	0.92
2008	0.94	1.00	0.84	0.05	0.83	0.93
2009	0.94	1.00	0.85	0.06	0.84	0.94
2010	0.94	1.00	0.82	0.03	0.79	0.88
2011	0.94	0.94	0.84	0.05	0.80	0.90
2012	0.94	1.00	0.84	0.05	0.80	0.89
2013	1.00	1.00	0.75	0.01	0.77	0.84
2014	1.00	1.00	0.83	0.04	0.82	0.89
2015	1.00	1.06	0.85	0.07	0.86	0.93
2016	0.94	1.00	0.82	0.03	0.82	0.92
2017	1.00	1.06	0.80	0.02	0.83	0.89
2018	1.00	1.06	0.81	0.02	0.83	0.90
2019	1.00	1.00	0.79	0.02	0.81	0.88

#1b. Overestimate M/k (*1.25):

lb_tableSH(freq, 2, "cm", linf=Linf, lmat=Lmat, mk_ratio=MK*1.25,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1997	0.88	0.94	0.82	0.19	0.93	1.00
1998	0.88	0.94	0.78	0.10	0.89	0.96
1999	0.94	1.00	0.80	0.14	0.94	0.97
2000	1.00	1.00	0.80	0.14	0.97	0.96
2001	0.94	1.00	0.82	0.18	0.97	0.99
2002	0.94	1.00	0.83	0.24	0.99	1.02
2003	0.94	1.00	0.83	0.30	1.00	1.03
2004	0.94	1.00	0.82	0.20	0.94	0.97
2005	0.94	1.00	0.82	0.22	0.96	0.99
2006	0.94	0.94	0.81	0.16	0.94	0.97
2007	0.94	1.00	0.83	0.20	0.96	0.99
2008	0.94	1.00	0.84	0.24	0.97	1.00
2009	0.94	1.00	0.85	0.25	0.98	1.01
2010	0.94	1.00	0.82	0.13	0.93	0.96
2011	0.94	0.94	0.84	0.18	0.94	0.97
2012	0.94	1.00	0.84	0.17	0.94	0.96
2013	1.00	1.00	0.75	0.05	0.91	0.90
2014	1.00	1.00	0.83	0.15	0.96	0.95
2015	1.00	1.06	0.85	0.28	1.01	1.00
2016	0.94	1.00	0.82	0.19	0.96	0.99
2017	1.00	1.06	0.80	0.16	0.97	0.96
2018	1.00	1.06	0.81	0.18	0.97	0.96
2019	1.00	1.00	0.79	0.13	0.96	0.95

#1c. M/k default value (1.5)

lb_tableSH(freq, 2, "cm", linf=Linf, lmat=Lmat, mk_ratio=1.5,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1997	0.88	0.94	0.82	0.11	0.88	0.98
1998	0.88	0.94	0.78	0.04	0.84	0.93
1999	0.94	1.00	0.80	0.07	0.89	0.95
2000	1.00	1.00	0.80	0.06	0.91	0.94
2001	0.94	1.00	0.82	0.09	0.91	0.97
2002	0.94	1.00	0.83	0.11	0.94	1.00
2003	0.94	1.00	0.83	0.13	0.94	1.01
2004	0.94	1.00	0.82	0.08	0.89	0.95
2005	0.94	1.00	0.82	0.11	0.90	0.96
2006	0.94	0.94	0.81	0.07	0.88	0.94
2007	0.94	1.00	0.83	0.11	0.91	0.97
2008	0.94	1.00	0.84	0.14	0.92	0.98
2009	0.94	1.00	0.85	0.16	0.93	0.99
2010	0.94	1.00	0.82	0.08	0.87	0.93
2011	0.94	0.94	0.84	0.12	0.89	0.95
2012	0.94	1.00	0.84	0.11	0.88	0.94
2013	1.00	1.00	0.75	0.02	0.86	0.88
2014	1.00	1.00	0.83	0.08	0.91	0.93
2015	1.00	1.06	0.85	0.15	0.95	0.98
2016	0.94	1.00	0.82	0.09	0.91	0.97
2017	1.00	1.06	0.80	0.06	0.91	0.94
2018	1.00	1.06	0.81	0.07	0.92	0.94
2019	1.00	1.00	0.79	0.05	0.90	0.93

#2a. Underestimate Linf (*0.75):

lb_tableSH(freq, 2, "cm", linf=Linf*0.75, lmat=Lmat, mk_ratio=MK,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1997	0.88	0.94	1.09	0.52	1.15	1.08
1998	0.88	0.94	1.04	0.42	1.10	1.03
1999	0.94	1.00	1.07	0.61	1.17	1.05
2000	1.00	1.00	1.07	0.72	1.19	1.03
2001	0.94	1.00	1.09	0.70	1.19	1.07
2002	0.94	1.00	1.11	0.72	1.23	1.10
2003	0.94	1.00	1.11	0.69	1.24	1.11
2004	0.94	1.00	1.09	0.52	1.16	1.05
2005	0.94	1.00	1.10	0.57	1.18	1.06
2006	0.94	0.94	1.08	0.54	1.16	1.04
2007	0.94	1.00	1.11	0.62	1.19	1.07
2008	0.94	1.00	1.12	0.64	1.20	1.08
2009	0.94	1.00	1.13	0.69	1.21	1.09
2010	0.94	1.00	1.10	0.57	1.15	1.03
2011	0.94	0.94	1.12	0.50	1.16	1.05
2012	0.94	1.00	1.12	0.51	1.15	1.04
2013	1.00	1.00	1.00	0.45	1.12	0.97
2014	1.00	1.00	1.11	0.67	1.19	1.03
2015	1.00	1.06	1.13	0.79	1.25	1.08
2016	0.94	1.00	1.09	0.69	1.19	1.07
2017	1.00	1.06	1.07	0.80	1.20	1.04
2018	1.00	1.06	1.08	0.78	1.20	1.04
2019	1.00	1.00	1.06	0.74	1.18	1.02

#2b. Overestimate Linf (*1.25):

lb_tableSH(freq, 2, "cm", linf=Linf*1.25, lmat=Lmat, mk_ratio=MK,wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1997	0.88	0.94	0.65	0	0.69	0.87
1998	0.88	0.94	0.62	0	0.66	0.83
1999	0.94	1.00	0.64	0	0.70	0.85
2000	1.00	1.00	0.64	0	0.72	0.85
2001	0.94	1.00	0.65	0	0.71	0.87
2002	0.94	1.00	0.67	0	0.74	0.90
2003	0.94	1.00	0.67	0	0.74	0.90
2004	0.94	1.00	0.65	0	0.70	0.85
2005	0.94	1.00	0.66	0	0.71	0.87
2006	0.94	0.94	0.65	0	0.69	0.85
2007	0.94	1.00	0.67	0	0.71	0.87
2008	0.94	1.00	0.67	0	0.72	0.88
2009	0.94	1.00	0.68	0	0.73	0.89
2010	0.94	1.00	0.66	0	0.69	0.84
2011	0.94	0.94	0.67	0	0.70	0.85
2012	0.94	1.00	0.67	0	0.69	0.85
2013	1.00	1.00	0.60	0	0.67	0.80
2014	1.00	1.00	0.67	0	0.71	0.84
2015	1.00	1.06	0.68	0	0.75	0.88
2016	0.94	1.00	0.65	0	0.71	0.87
2017	1.00	1.06	0.64	0	0.72	0.85
2018	1.00	1.06	0.65	0	0.72	0.85
2019	1.00	1.00	0.64	0	0.71	0.84

Pouting

Parámetros ciclo vital que vamos usar para el Trisopterus luscus:

Usaremos como referencia de talla de primera maduración la referentecia para hembras de Alonso-Fernandez et al. (2008), \(L^{LIT}_{50} = 19.2 cm\), basado en histología.
Los parámetros de crecimiento (Von Bertalanffy) que se recogen en Labarta et al. (1982): \(L^{LIT}_{inf} = 46.7 cm\); \(K^{LIT} = 0.21\); \(t^{LIT}_{0} = 1.27\); \(A^{LIT}_{max} = 9 years\).
Para estimar el ratio \(M/K^{LIT}\) recurrimos a Then et al. (2015). Como referencia proponemos usar el cáculo de mortalidad natural basado en los parámetros de crecimiento (ver arriba): \(M_{VBGF} = 0.3699877 y^{-1}\); \(M_{VBGF}/K^{LIT} = 1.761846\). Pero además probaremos el método basado en la edad máxima: \(M_{nls} = 0.6533320 y^{-1}\); \(M_{nls}/K^{LIT} = 3.111105\).

# usaremos los datos de Von Bertalanfy calculados por Labarta et al. (1982)
# datos de maduración de Alonso-Fernández et al. (2008)
# En ambos casos usamos como referencia los datos de hembras
LHTs <- data.frame(t(c("Trisopterus luscus", 19.2, 1, 46.7, 0.21, 1.27, 9)))
colnames(LHTs) <- c("Sp", "L50", "A50", "Linf", "K", "t0", "Amax")

# Usando como referencia Then et al. (2015)
# proponemos usa 2 principales métodos de cálculo de mortalidad
# Then_nls y Then_VBGF
LHTs$MKvbgf <- 1.761846
LHTs$MKnls <- 3.111105
LHTs$MK <- 1.5



library(readr)
faneca <- read_csv("faneca_ieo.csv")
sizeDat <- na.omit(faneca %>%
                    select(TLength, Year))
anho <- as.character(unique(sort(faneca$Year)))
sizeDat <- data.frame(sizeDat)
br = seq(min(sizeDat$TLength), max(sizeDat$TLength) + 1, by = 1)
ranges = paste(head(br, -1), br[-1], sep = " - ")

sizeDat <- unstack(sizeDat)

freq <- data.frame(matrix(NA, nrow = length(br)-1, ncol = length(anho)+1))

for (i in 1:length(anho)) {
  freq[, 1] <- head(br, -1)
  freq[, i + 1] <-
    hist(
      sizeDat[[i]],
      breaks = br - 1,
      include.lowest = TRUE,
      plot = FALSE
    )$counts
  colnames(freq) <- c("MeanLength", anho)
}

head(freq)

##   MeanLength 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
## 1         10    0    0    0    0    0    1    0    0    0    0    0    0    0
## 2         11    0    0    0    0    0    1    0    0    0    0    0    0    0
## 3         12    0    0    1    0    0    0    0    0    0    0    0    0    0
## 4         13    0    0    0    2    1    1    0    2    4    2    0    0    1
## 5         14    0    2    5    5    2    2    1    2   12    1    1    1    0
## 6         15    0    0    8    3   14    2   10    2   18    0    3    1    6
##   2012 2013 2014 2015 2016 2017 2018
## 1    0    0    1    0    0    0    0
## 2    0    0    0    0    0    2    0
## 3    0    0    0    0    0    1    0
## 4    0    0    1    0    0    0    0
## 5    0    2    0    0    0    3    2
## 6    1    3    5    9    3    3    5

freq[,1]=seq(10.5,43.5)
br=seq(10.5,43.5)


alfaWL=0.01303439
betaWL=2.969518



wal <- freq


for (i in 2:dim(freq)[2]) {
  wal[, i] <- alfaWL * ((br) ^ betaWL)
}
colnames(wal) <- c("MeanLength", anho)
head(wal)

##   MeanLength     1999     2000     2001     2002     2003     2004     2005
## 1       10.5 14.04529 14.04529 14.04529 14.04529 14.04529 14.04529 14.04529
## 2       11.5 18.40145 18.40145 18.40145 18.40145 18.40145 18.40145 18.40145
## 3       12.5 23.57137 23.57137 23.57137 23.57137 23.57137 23.57137 23.57137
## 4       13.5 29.62356 29.62356 29.62356 29.62356 29.62356 29.62356 29.62356
## 5       14.5 36.62637 36.62637 36.62637 36.62637 36.62637 36.62637 36.62637
## 6       15.5 44.64801 44.64801 44.64801 44.64801 44.64801 44.64801 44.64801
##       2006     2007     2008     2009     2010     2011     2012     2013
## 1 14.04529 14.04529 14.04529 14.04529 14.04529 14.04529 14.04529 14.04529
## 2 18.40145 18.40145 18.40145 18.40145 18.40145 18.40145 18.40145 18.40145
## 3 23.57137 23.57137 23.57137 23.57137 23.57137 23.57137 23.57137 23.57137
## 4 29.62356 29.62356 29.62356 29.62356 29.62356 29.62356 29.62356 29.62356
## 5 36.62637 36.62637 36.62637 36.62637 36.62637 36.62637 36.62637 36.62637
## 6 44.64801 44.64801 44.64801 44.64801 44.64801 44.64801 44.64801 44.64801
##       2014     2015     2016     2017     2018
## 1 14.04529 14.04529 14.04529 14.04529 14.04529
## 2 18.40145 18.40145 18.40145 18.40145 18.40145
## 3 23.57137 23.57137 23.57137 23.57137 23.57137
## 4 29.62356 29.62356 29.62356 29.62356 29.62356
## 5 36.62637 36.62637 36.62637 36.62637 36.62637
## 6 44.64801 44.64801 44.64801 44.64801 44.64801

bin_plot(freq, 1, "cm")

lb_tableSH(freq, 1, "cm", 46.7 , 19.2, 1.761846, wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1999	1.07	1.12	0.65	0.00	0.79	0.89
2000	0.96	1.02	0.60	0.00	0.74	0.88
2001	0.91	1.02	0.64	0.01	0.75	0.92
2002	0.96	1.02	0.65	0.01	0.77	0.92
2003	0.96	1.07	0.65	0.01	0.78	0.92
2004	1.02	1.07	0.62	0.00	0.78	0.90
2005	0.96	1.02	0.63	0.00	0.76	0.90
2006	0.96	1.02	0.63	0.00	0.75	0.89
2007	0.96	1.02	0.62	0.00	0.75	0.89
2008	1.02	1.02	0.60	0.00	0.75	0.87
2009	1.02	1.07	0.63	0.00	0.78	0.89
2010	1.02	1.02	0.66	0.01	0.75	0.87
2011	0.96	1.02	0.63	0.01	0.75	0.89
2012	1.02	1.07	0.63	0.00	0.76	0.88
2013	0.96	1.02	0.58	0.00	0.73	0.87
2014	1.02	1.07	0.59	0.00	0.75	0.87
2015	1.02	1.07	0.68	0.02	0.80	0.92
2016	1.02	1.07	0.63	0.01	0.76	0.88
2017	1.02	1.07	0.63	0.00	0.78	0.90
2018	1.02	1.07	0.63	0.00	0.78	0.89

lb_tableSH(freq, 1,"cm",46.7 , 19.2, 0.75*1.761846, wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1999	1.07	1.12	0.65	0	0.72	0.84
2000	0.96	1.02	0.60	0	0.67	0.83
2001	0.91	1.02	0.64	0	0.68	0.86
2002	0.96	1.02	0.65	0	0.70	0.87
2003	0.96	1.07	0.65	0	0.70	0.87
2004	1.02	1.07	0.62	0	0.70	0.85
2005	0.96	1.02	0.63	0	0.69	0.85
2006	0.96	1.02	0.63	0	0.68	0.84
2007	0.96	1.02	0.62	0	0.68	0.84
2008	1.02	1.02	0.60	0	0.68	0.82
2009	1.02	1.07	0.63	0	0.70	0.85
2010	1.02	1.02	0.66	0	0.68	0.82
2011	0.96	1.02	0.63	0	0.68	0.84
2012	1.02	1.07	0.63	0	0.69	0.83
2013	0.96	1.02	0.58	0	0.66	0.82
2014	1.02	1.07	0.59	0	0.68	0.82
2015	1.02	1.07	0.68	0	0.73	0.87
2016	1.02	1.07	0.63	0	0.69	0.83
2017	1.02	1.07	0.63	0	0.71	0.85
2018	1.02	1.07	0.63	0	0.70	0.85

lb_tableSH(freq, 1,"cm",46.7 , 19.2, 1.25*1.761846, wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1999	1.07	1.12	0.65	0.03	0.87	0.92
2000	0.96	1.02	0.60	0.01	0.81	0.92
2001	0.91	1.02	0.64	0.02	0.82	0.96
2002	0.96	1.02	0.65	0.02	0.84	0.96
2003	0.96	1.07	0.65	0.02	0.85	0.96
2004	1.02	1.07	0.62	0.01	0.85	0.93
2005	0.96	1.02	0.63	0.01	0.83	0.94
2006	0.96	1.02	0.63	0.02	0.82	0.93
2007	0.96	1.02	0.62	0.01	0.82	0.93
2008	1.02	1.02	0.60	0.01	0.82	0.90
2009	1.02	1.07	0.63	0.01	0.85	0.93
2010	1.02	1.02	0.66	0.03	0.82	0.90
2011	0.96	1.02	0.63	0.01	0.82	0.93
2012	1.02	1.07	0.63	0.01	0.84	0.92
2013	0.96	1.02	0.58	0.00	0.80	0.90
2014	1.02	1.07	0.59	0.01	0.82	0.90
2015	1.02	1.07	0.68	0.04	0.87	0.96
2016	1.02	1.07	0.63	0.01	0.83	0.91
2017	1.02	1.07	0.63	0.02	0.85	0.94
2018	1.02	1.07	0.63	0.02	0.85	0.93

lb_tableSH(freq, 1,"cm",46.7 , 19.2, 1.5, wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1999	1.07	1.12	0.65	0	0.75	0.86
2000	0.96	1.02	0.60	0	0.70	0.85
2001	0.91	1.02	0.64	0	0.71	0.89
2002	0.96	1.02	0.65	0	0.73	0.89
2003	0.96	1.07	0.65	0	0.73	0.89
2004	1.02	1.07	0.62	0	0.73	0.87
2005	0.96	1.02	0.63	0	0.72	0.87
2006	0.96	1.02	0.63	0	0.71	0.86
2007	0.96	1.02	0.62	0	0.71	0.86
2008	1.02	1.02	0.60	0	0.71	0.84
2009	1.02	1.07	0.63	0	0.73	0.87
2010	1.02	1.02	0.66	0	0.71	0.84
2011	0.96	1.02	0.63	0	0.71	0.86
2012	1.02	1.07	0.63	0	0.72	0.86
2013	0.96	1.02	0.58	0	0.69	0.84
2014	1.02	1.07	0.59	0	0.71	0.84
2015	1.02	1.07	0.68	0	0.76	0.90
2016	1.02	1.07	0.63	0	0.72	0.85
2017	1.02	1.07	0.63	0	0.74	0.87
2018	1.02	1.07	0.63	0	0.73	0.87

lb_tableSH(freq, 1,"cm",0.75*46.7 , 19.2, 1.761846, wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1999	1.07	1.12	0.87	0.27	1.06	0.99
2000	0.96	1.02	0.80	0.14	0.99	0.98
2001	0.91	1.02	0.86	0.23	1.00	1.03
2002	0.96	1.02	0.86	0.27	1.03	1.03
2003	0.96	1.07	0.87	0.29	1.04	1.03
2004	1.02	1.07	0.82	0.28	1.04	1.00
2005	0.96	1.02	0.84	0.22	1.01	1.01
2006	0.96	1.02	0.84	0.19	1.00	0.99
2007	0.96	1.02	0.82	0.18	1.00	0.99
2008	1.02	1.02	0.80	0.16	1.00	0.96
2009	1.02	1.07	0.84	0.25	1.03	0.99
2010	1.02	1.02	0.88	0.15	1.00	0.97
2011	0.96	1.02	0.84	0.15	1.00	0.99
2012	1.02	1.07	0.84	0.21	1.02	0.98
2013	0.96	1.02	0.77	0.13	0.97	0.97
2014	1.02	1.07	0.79	0.15	1.00	0.97
2015	1.02	1.07	0.90	0.37	1.07	1.03
2016	1.02	1.07	0.84	0.20	1.02	0.98
2017	1.02	1.07	0.85	0.27	1.04	1.00
2018	1.02	1.07	0.84	0.24	1.03	1.00

lb_tableSH(freq, 1,"cm",1.25*46.7 , 19.2, 1.761846, wal)

	Conservation				Optimizing Yield	MSY
Year	Lc / Lmat	L25% / Lmat	Lmax 5 / Linf	Pmega	Lmean / Lopt	Lmean / LF = M
1999	1.07	1.12	0.52	0	0.64	0.81
2000	0.96	1.02	0.48	0	0.59	0.80
2001	0.91	1.02	0.52	0	0.60	0.83
2002	0.96	1.02	0.52	0	0.62	0.83
2003	0.96	1.07	0.52	0	0.62	0.84
2004	1.02	1.07	0.49	0	0.62	0.81
2005	0.96	1.02	0.50	0	0.61	0.82
2006	0.96	1.02	0.50	0	0.60	0.81
2007	0.96	1.02	0.49	0	0.60	0.81
2008	1.02	1.02	0.48	0	0.60	0.79
2009	1.02	1.07	0.50	0	0.62	0.81
2010	1.02	1.02	0.53	0	0.60	0.79
2011	0.96	1.02	0.51	0	0.60	0.80
2012	1.02	1.07	0.50	0	0.61	0.80
2013	0.96	1.02	0.46	0	0.58	0.79
2014	1.02	1.07	0.47	0	0.60	0.79
2015	1.02	1.07	0.54	0	0.64	0.84
2016	1.02	1.07	0.51	0	0.61	0.80
2017	1.02	1.07	0.51	0	0.63	0.82
2018	1.02	1.07	0.51	0	0.62	0.81

LBI

Marta Cousido

3/11/2020

LBI all the species together.

Norway Loster 8c FU25

Norway Loster 8c FU25 Males

Norway Loster 8c FU25 Females

Norway Loster FU2627

Norway Loster FU2627 Males

Norway Loster FU2627 Females

Small Spotted Catshark

Anchovy

Pollack

Blackspot Seabream

Pouting